From 7a6c34c2a2541432c50b6f9b994186c908f469bc Mon Sep 17 00:00:00 2001 From: github-actions Date: Thu, 12 Sep 2024 06:59:47 +0000 Subject: [PATCH] Update web --- 404.html | 2 +- about.html | 2 +- beyond-data-management-plans.html | 2 +- biodata-pt-experience.html | 2 +- comparison.html | 2 +- contact.html | 2 +- cookie-policy.html | 2 +- data-management-plans.html | 2 +- data-steward.html | 2 +- data-stewardship.html | 2 +- dmponline-alternative.html | 2 +- document-templates.html | 2 +- dsw-story.html | 2 +- elixir-norway-dsw-story.html | 2 +- enabling-seamless-dmp-within-panocs.html | 2 +- enterprise.html | 2 +- fair.html | 2 +- funder.html | 2 +- get-started.html | 2 +- help-center.html | 2 +- index.html | 2 +- integrating-dsw-at-ifb.html | 2 +- integrations.html | 2 +- knowledge-models.html | 2 +- machine-actionability.html | 2 +- media.html | 2 +- researcher.html | 2 +- resources.html | 2 +- scilifelab-dsw-story.html | 2 +- sitemap.xml | 2 +- sitemap.xml.gz | Bin 579 -> 579 bytes story-dsw-clermont-auvergne-university.html | 2 +- success-stories.html | 2 +- the-chalmers-ds-wizard-story.html | 2 +- translate-dsw.html | 2 +- university.html | 2 +- video-tutorials.html | 2 +- 37 files changed, 36 insertions(+), 36 deletions(-) diff --git a/404.html b/404.html index f572de8..070766d 100644 --- a/404.html +++ b/404.html @@ -1 +1 @@ -Not found | Data Stewardship Wizard
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\ No newline at end of file diff --git a/about.html b/about.html index cc99035..3837bea 100644 --- a/about.html +++ b/about.html @@ -1 +1 @@ -About | Data Stewardship Wizard
DSW
Get Started
DSW
Get Started

About

We bring together data stewards and researchers to efficiently compose data management plans (DMPs) for their research projects.

DSW Logo

Data Stewards capture and combine their knowledge and expertise with respect to the specific needs of a domain or an organisation. Researchers are truly guided through composing a DMP which can be then exported using selected template and format, including machine-actionable. The benefit lies not only in having a nowadays often obligatory DMP for funders but mainly learning how to handle data correctly, make them FAIR, maintain them well during the project, and curate them long-term.

The DSW Story

The DSW story originates in the Netherlands where Dr Rob Hooft of the Dutch Techcentre for Lifesciences (DTL) started collecting knowledge about data stewardship around 2012, when taking part in discussions on the introduction of Data Management Plans by national funder ZonMw, and formalised it in the form of a hierarchical mind map...

Read the full story

The DSW Core Team

Robert Pergl
Robert PerglProject Coordinator
Rob Hooft
Rob HooftDS Knowledge Expert
Jiří Vondrášek
Jiří VondrášekBusiness and Strategic Advisory
Vojtěch Knaisl
Vojtěch KnaislBackend Developer
Jan Slifka
Jan SlifkaFrontend Developer
Marek Suchánek
Marek SuchánekLeonardo da Vinci
Jana Freeman
Jana FreemanCommunity Manager
Kryštof Komanec
Kryštof KomanecKnowledge Steward & Trainer
Jana Martínková
Jana MartínkováOntology Engineer
Georgia Koutentaki
Georgia KoutentakiData Steward
David Šenkýř
David ŠenkýřNLP & AI Specialist
Hana Litavská
Hana LitavskáDatabase Specialist

Advisory Board

DSW Advisory Board is a non-decision making body composed of industry leaders, prominent experts and academics specialized in the field of data management planning, data stewardship, data fairification, and other related fields. DSW Advisory Board's mission is to support and advise the DSW core team to steer the DSW development, adoption of the DSW by a broad community, and embedding it in practice.

Pinar Alper
Pinar AlperELIXIR Luxembourg
Korbinian Bösl
Korbinian BöslELIXIR Norway, Centre for Digital Life Norway, Computational Biological Unit - University of Bergen
Flora D'Anna
Flora D'AnnaELIXIR Belgium, VIB-UGent Center for Plant Systems Biology
Carole Goble
Carole GobleThe University of Manchester, Joint Head of Node ELIXIR-UK
Kristina Hettne
Kristina HettneCentre for Digital Scholarship, Leiden University Libraries
Niclas Jareborg
Niclas JareborgELIXIR Sweden, National Bioinformatics Infrastructure Sweden
Yvonne Kallberg
Yvonne KallbergELIXIR Sweden, National Bioinformatics Infrastructure Sweden
Brane Leskošek
Brane LeskošekELIXIR Slovenia, University of Ljubljana, Faculty of Medicine, IBMI
Barbara Magagna
Barbara MagagnaEnvironment Agency Austria
Tomasz Miksa
Tomasz MiksaTU Wien & SBA Research
Barend Mons
Barend MonsGO FAIR
João Moreira
João MoreiraUniversity of Twente
Valentina Pasquale
Valentina PasqualeIstituto Italiano di Tecnologia
Martin Schätz
Martin SchätzGloBIAS, National Library of Technology & University of Chemistry and Technology in Prague
Erik Schultes
Erik SchultesGO FAIR
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
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\ No newline at end of file +About | Data Stewardship Wizard
DSW
Get Started
DSW
Get Started

About

We bring together data stewards and researchers to efficiently compose data management plans (DMPs) for their research projects.

DSW Logo

Data Stewards capture and combine their knowledge and expertise with respect to the specific needs of a domain or an organisation. Researchers are truly guided through composing a DMP which can be then exported using selected template and format, including machine-actionable. The benefit lies not only in having a nowadays often obligatory DMP for funders but mainly learning how to handle data correctly, make them FAIR, maintain them well during the project, and curate them long-term.

The DSW Story

The DSW story originates in the Netherlands where Dr Rob Hooft of the Dutch Techcentre for Lifesciences (DTL) started collecting knowledge about data stewardship around 2012, when taking part in discussions on the introduction of Data Management Plans by national funder ZonMw, and formalised it in the form of a hierarchical mind map...

Read the full story

The DSW Core Team

Robert Pergl
Robert PerglProject Coordinator
Rob Hooft
Rob HooftDS Knowledge Expert
Jiří Vondrášek
Jiří VondrášekBusiness and Strategic Advisory
Vojtěch Knaisl
Vojtěch KnaislBackend Developer
Jan Slifka
Jan SlifkaFrontend Developer
Marek Suchánek
Marek SuchánekLeonardo da Vinci
Jana Freeman
Jana FreemanCommunity Manager
Kryštof Komanec
Kryštof KomanecKnowledge Steward & Trainer
Jana Martínková
Jana MartínkováOntology Engineer
Georgia Koutentaki
Georgia KoutentakiData Steward
David Šenkýř
David ŠenkýřNLP & AI Specialist
Hana Litavská
Hana LitavskáDatabase Specialist

Advisory Board

DSW Advisory Board is a non-decision making body composed of industry leaders, prominent experts and academics specialized in the field of data management planning, data stewardship, data fairification, and other related fields. DSW Advisory Board's mission is to support and advise the DSW core team to steer the DSW development, adoption of the DSW by a broad community, and embedding it in practice.

Pinar Alper
Pinar AlperELIXIR Luxembourg
Korbinian Bösl
Korbinian BöslELIXIR Norway, Centre for Digital Life Norway, Computational Biological Unit - University of Bergen
Flora D'Anna
Flora D'AnnaELIXIR Belgium, VIB-UGent Center for Plant Systems Biology
Carole Goble
Carole GobleThe University of Manchester, Joint Head of Node ELIXIR-UK
Kristina Hettne
Kristina HettneCentre for Digital Scholarship, Leiden University Libraries
Niclas Jareborg
Niclas JareborgELIXIR Sweden, National Bioinformatics Infrastructure Sweden
Yvonne Kallberg
Yvonne KallbergELIXIR Sweden, National Bioinformatics Infrastructure Sweden
Brane Leskošek
Brane LeskošekELIXIR Slovenia, University of Ljubljana, Faculty of Medicine, IBMI
Barbara Magagna
Barbara MagagnaEnvironment Agency Austria
Tomasz Miksa
Tomasz MiksaTU Wien & SBA Research
Barend Mons
Barend MonsGO FAIR
João Moreira
João MoreiraUniversity of Twente
Valentina Pasquale
Valentina PasqualeIstituto Italiano di Tecnologia
Martin Schätz
Martin SchätzGloBIAS, National Library of Technology & University of Chemistry and Technology in Prague
Erik Schultes
Erik SchultesGO FAIR
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\ No newline at end of file diff --git a/beyond-data-management-plans.html b/beyond-data-management-plans.html index 847657a..0c4099e 100644 --- a/beyond-data-management-plans.html +++ b/beyond-data-management-plans.html @@ -1 +1 @@ -Beyond Data Management Plans | Data Stewardship Wizard
DSW
Get Started
DSW
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Beyond Data Management Plans

Data Stewardship Wizard is a very flexible tool allowing you to create knowledge models and document templates related to domains other than data stewardship and DMPs. It can easily be shaped into any expert system that an organisation or community needs. There are already such use cases beyond data management plans realised in practice, and we expect more to be coming over time.

Beyond Data Management Plans Illustration

Software Management Plans

In ELIXIR, significant work is being done on software management planning. We are currently collaborating on shaping DSW into SMW (Software Management Wizard). The Software development best practices for Life Sciences group is working on the content side, more specifically a knowledge model and integration, and we are providing our expertise to push SMW into production-ready status.

Software Management Plans

FAIR Data Entry Tool of VODAN-in-a-Box

During the COVID-19 outbreak, DSW became part of VODAN-in-a-Box proof-of-concept solution to address FAIR data capture of patient data. A knowledge model based on the WHO COVID-19 Case Report Form has been designed and linked to a semantic model supported by an OWL ontology. The ontology served in a document template for transforming the forms into RDF format to enable machine-actionability. The solution allows users to submit a report form in RDF into a dedicated triple store which can be used for (distributed) SPARQL queries and further analysis.

FAIR Data Entry Tool of VODAN-in-a-Box

FIP Wizard

FIP Wizard allows one to compose so-called FAIR Implementation Profiles that capture community choices of FAIR-enabling resources, i.e., how a community implements FAIR. The FIP structure is encoded as a knowledge model. Moreover, a document template is created to export FIPs in machine-actionable nanopublications (RDF-based). Finally, it is possible to send such a nanopublication directly to a distributed network of nanopublication services using a submission service.

FIP Wizard
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\ No newline at end of file +Beyond Data Management Plans | Data Stewardship Wizard
DSW
Get Started
DSW
Get Started

Beyond Data Management Plans

Data Stewardship Wizard is a very flexible tool allowing you to create knowledge models and document templates related to domains other than data stewardship and DMPs. It can easily be shaped into any expert system that an organisation or community needs. There are already such use cases beyond data management plans realised in practice, and we expect more to be coming over time.

Beyond Data Management Plans Illustration

Software Management Plans

In ELIXIR, significant work is being done on software management planning. We are currently collaborating on shaping DSW into SMW (Software Management Wizard). The Software development best practices for Life Sciences group is working on the content side, more specifically a knowledge model and integration, and we are providing our expertise to push SMW into production-ready status.

Software Management Plans

FAIR Data Entry Tool of VODAN-in-a-Box

During the COVID-19 outbreak, DSW became part of VODAN-in-a-Box proof-of-concept solution to address FAIR data capture of patient data. A knowledge model based on the WHO COVID-19 Case Report Form has been designed and linked to a semantic model supported by an OWL ontology. The ontology served in a document template for transforming the forms into RDF format to enable machine-actionability. The solution allows users to submit a report form in RDF into a dedicated triple store which can be used for (distributed) SPARQL queries and further analysis.

FAIR Data Entry Tool of VODAN-in-a-Box

FIP Wizard

FIP Wizard allows one to compose so-called FAIR Implementation Profiles that capture community choices of FAIR-enabling resources, i.e., how a community implements FAIR. The FIP structure is encoded as a knowledge model. Moreover, a document template is created to export FIPs in machine-actionable nanopublications (RDF-based). Finally, it is possible to send such a nanopublication directly to a distributed network of nanopublication services using a submission service.

FIP Wizard
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\ No newline at end of file diff --git a/biodata-pt-experience.html b/biodata-pt-experience.html index dda7a54..a7d87ca 100644 --- a/biodata-pt-experience.html +++ b/biodata-pt-experience.html @@ -1 +1 @@ -BioData.pt Experience | Data Stewardship Wizard
DSW
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DSW
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BioData.pt experience with DSW

What is BioData.pt

BioData.pt is the Portuguese distributed e-infrastructure for biological data and the Portuguese ELIXIR node. Its mission is to support the national scientific system through best practices in data management and state of the art data analysis. It interfaces with both academia and industry, making research available for innovation, namely in sectors such as agro-food and forestry, sea, and health.

What does BioData.pt do?

In compliance with its mission, BioData.pt provides three types of Data Management Services: (1) Project Data Management. Focusing on providing consulting services in data management; (2) The Data Management Portal. A digital library for the hosting of data from the BioData.pt communities; and (3) The Ready For BioData Management programme. A capacity building programme to empower researchers in data management.

What are BioData.pt’s plans for the DSW?

The Data Stewardship Wizard was brought in as a DMP creation tool to be used in the context of the Ready For BioData Management programme. Currently the course is being revised to operate fully online, with events being scheduled to the first quarter of 2021. The DSW will play a key role in its operation, by allowing participants to use BioData.pt’s DSW instance to create DMP documents based on real projects.

What are our future goals?

Some of our research team has also been collaborating with the DSW to develop the DSCO RDF/XML extraction format. Our goal for the future is to have these serialisations of DMP document be used by automated systems to enact data management activities.

João Cardoso, INESC-ID & BioData.pt, Lisbon, Portugal

BioData.pt logo
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\ No newline at end of file +BioData.pt Experience | Data Stewardship Wizard
DSW
Get Started
DSW
Get Started

BioData.pt experience with DSW

What is BioData.pt

BioData.pt is the Portuguese distributed e-infrastructure for biological data and the Portuguese ELIXIR node. Its mission is to support the national scientific system through best practices in data management and state of the art data analysis. It interfaces with both academia and industry, making research available for innovation, namely in sectors such as agro-food and forestry, sea, and health.

What does BioData.pt do?

In compliance with its mission, BioData.pt provides three types of Data Management Services: (1) Project Data Management. Focusing on providing consulting services in data management; (2) The Data Management Portal. A digital library for the hosting of data from the BioData.pt communities; and (3) The Ready For BioData Management programme. A capacity building programme to empower researchers in data management.

What are BioData.pt’s plans for the DSW?

The Data Stewardship Wizard was brought in as a DMP creation tool to be used in the context of the Ready For BioData Management programme. Currently the course is being revised to operate fully online, with events being scheduled to the first quarter of 2021. The DSW will play a key role in its operation, by allowing participants to use BioData.pt’s DSW instance to create DMP documents based on real projects.

What are our future goals?

Some of our research team has also been collaborating with the DSW to develop the DSCO RDF/XML extraction format. Our goal for the future is to have these serialisations of DMP document be used by automated systems to enact data management activities.

João Cardoso, INESC-ID & BioData.pt, Lisbon, Portugal

BioData.pt logo
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file diff --git a/comparison.html b/comparison.html index 33cf0b0..e5c3390 100644 --- a/comparison.html +++ b/comparison.html @@ -1 +1 @@ -DSW Compared to Other DMP Tools | Data Stewardship Wizard
DSW
Get Started
DSW
Get Started

DSW Compared to Other DMP Tools

DSWDMPonlineDMPToolArgosDataWizeasyDMP
Template SelectionLimited
Detailed Export SettingsLimitedLimited
Template CreationLimited
Template Styling
Project PhasesUnknownLimited
Suitable For Worldwide UseLimitedLimitedLimitedLimitedLimited
Various Sharing OptionsLimitedLimitedLimitedLimited
Comments
Machine-ActionabilityLimitedLimitedLimitedLimited
FAIR Metrics InformationLimitedLimited
TODOs
Live Collaboration
MigrationsUnknownUnknown
Version HistoryUnknownUnknownLimitedLimitedUnknown
Languages (other than English)Limited
Funder TemplatesLimitedLimited

Information relevant to April of 2023.

Disclaimer: This comparison of free / no-need-to-contact versions of the tools is only informative and it is not presented as a rigorous result of a scientific study. Please note that all the comparisons mentioned herewith have been compiled based on information available on the tool's official websites. Also note that the meanings of comparisons are given in detail below the table and depict how DSW understands and standardly uses them, they therefore can differ from how they are understood and used by other tools.

Template Selection

One of the key needs is the possibility to choose a questionnaire template from an existing list of templates. These templates can be both well-known templates of important funders and templates created for specific situations and projects.

Learn more

Detailed Export Settings

"The more languages you speak, the more times you are human." Or the less known equivalent of this valid for the Data Stewardship Wizard, "The more export formats you know, the more times you make users happy."

Learn more

Template Creation

It is not possible to have the perfect template for every person and situation. That is why we offer you the option to create your own template based on your specific use case.

Learn more

Template Styling

If you need to style your template with a logo of your organization, use a different font or specific header or footer, as an administrator you can set it up by yourself. If you have any difficulties to do so, there is a Template Development Kit tutorial video to help you out!

Learn more

Project Phases

We know that you might not know all the answers to all questions at the time of creation of the data management plan. That is the reason why we support project phases, to help you answer all the questions over time.

Learn more

Suitable For Worldwide Use

While some tools are local installations and thus may lack full support or some important templates, with the Data Stewardship Wizard you do not have to worry about it. Our questionnaires are completely independent of the template hence the country as well. You can generate a DMP in different templates for one questionnaire without the need to rewrite it!

Various Sharing Options

You can set the visibility settings to be completely private, or allow users to view your project or edit it. Moreover, you can make the questionnaire link available even for non-logged users, share it with them, and start to collaborate.

Learn more

Comments

While working with other users on your DMP, you can write comments to discuss some questions and issues.

Learn more

Machine-Actionability

Some work can be done by machines and that can save the time of many people and also make things easier. Unlike working with blocks of text that are hard to read and work with for machines, the Data Stewardship Wizard was developed to use a bare minimum of free text and uses UUID for each question and answers in its machine-actionable DMPs so that machines can read them easily and decide accordingly to spare your time and effort.

Learn more

FAIR Metrics Information

Following the recommendations of the GO FAIR initiative and good data management plan practices can be difficult and overwhelming. The Data Stewardship Wizard helps by providing summary reports of FAIR metrics based on your answers. To make it even easier, it also shows which answers should be preferred according to these recommendations and metrics.

Learn more

TODOs

With our To Do labels you do not have to worry anymore about not being able to answer every question at the moment. You can just mark it and answer it later through your TODOs list.

Live Collaboration

Everything is better with friends! In the DSW, multiple users can fill the DMP at the same time and see the changes made by others in real-time. Just like you would expect it in a cutting-edge online platform.

Learn more

Migrations

Life is change and we know that the specifications for your data management plan can also change at any time during the Project. In that case, with DSW there is no need to start all over again! Simply use the option of Migration and update your Project easily to a new version or even a different Knowledge Model. Moreover, when you have customization of a Knowledge Model that has been updated, you can easily migrate the customization to a newer version of the parent Knowledge Model as well.

Learn more

Version History

In DSW, every change you make in your project is saved. Furthermore, it also allows you to browse the history, watch who made changes and when, and create a version for your project's specific state. Working on the project with a group of people or having lots of changes in the project over time, the version history will definitely make your life easier!

Languages (other than English)

The Data Stewardship Wizard is provided in English by default. While we believe that in today's world, the English language is essential and accepted as the primary language for creating DMPs, it is possible to localize DSW to any other language. We run localize.ds-wizard.org, where the community can work together on different localizations, and the results are published in DSW Registry.

Funder Templates

We are working on increasing the number of Funder templates that the DSW offers, so you can easily use them while applying your project at the most common funding agencies. It takes a lot of work but we are looking forward to presenting you more funder templates soon!

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file +DSW Compared to Other DMP Tools | Data Stewardship Wizard
DSW
Get Started
DSW
Get Started

DSW Compared to Other DMP Tools

DSWDMPonlineDMPToolArgosDataWizeasyDMP
Template SelectionLimited
Detailed Export SettingsLimitedLimited
Template CreationLimited
Template Styling
Project PhasesUnknownLimited
Suitable For Worldwide UseLimitedLimitedLimitedLimitedLimited
Various Sharing OptionsLimitedLimitedLimitedLimited
Comments
Machine-ActionabilityLimitedLimitedLimitedLimited
FAIR Metrics InformationLimitedLimited
TODOs
Live Collaboration
MigrationsUnknownUnknown
Version HistoryUnknownUnknownLimitedLimitedUnknown
Languages (other than English)Limited
Funder TemplatesLimitedLimited

Information relevant to April of 2023.

Disclaimer: This comparison of free / no-need-to-contact versions of the tools is only informative and it is not presented as a rigorous result of a scientific study. Please note that all the comparisons mentioned herewith have been compiled based on information available on the tool's official websites. Also note that the meanings of comparisons are given in detail below the table and depict how DSW understands and standardly uses them, they therefore can differ from how they are understood and used by other tools.

Template Selection

One of the key needs is the possibility to choose a questionnaire template from an existing list of templates. These templates can be both well-known templates of important funders and templates created for specific situations and projects.

Learn more

Detailed Export Settings

"The more languages you speak, the more times you are human." Or the less known equivalent of this valid for the Data Stewardship Wizard, "The more export formats you know, the more times you make users happy."

Learn more

Template Creation

It is not possible to have the perfect template for every person and situation. That is why we offer you the option to create your own template based on your specific use case.

Learn more

Template Styling

If you need to style your template with a logo of your organization, use a different font or specific header or footer, as an administrator you can set it up by yourself. If you have any difficulties to do so, there is a Template Development Kit tutorial video to help you out!

Learn more

Project Phases

We know that you might not know all the answers to all questions at the time of creation of the data management plan. That is the reason why we support project phases, to help you answer all the questions over time.

Learn more

Suitable For Worldwide Use

While some tools are local installations and thus may lack full support or some important templates, with the Data Stewardship Wizard you do not have to worry about it. Our questionnaires are completely independent of the template hence the country as well. You can generate a DMP in different templates for one questionnaire without the need to rewrite it!

Various Sharing Options

You can set the visibility settings to be completely private, or allow users to view your project or edit it. Moreover, you can make the questionnaire link available even for non-logged users, share it with them, and start to collaborate.

Learn more

Comments

While working with other users on your DMP, you can write comments to discuss some questions and issues.

Learn more

Machine-Actionability

Some work can be done by machines and that can save the time of many people and also make things easier. Unlike working with blocks of text that are hard to read and work with for machines, the Data Stewardship Wizard was developed to use a bare minimum of free text and uses UUID for each question and answers in its machine-actionable DMPs so that machines can read them easily and decide accordingly to spare your time and effort.

Learn more

FAIR Metrics Information

Following the recommendations of the GO FAIR initiative and good data management plan practices can be difficult and overwhelming. The Data Stewardship Wizard helps by providing summary reports of FAIR metrics based on your answers. To make it even easier, it also shows which answers should be preferred according to these recommendations and metrics.

Learn more

TODOs

With our To Do labels you do not have to worry anymore about not being able to answer every question at the moment. You can just mark it and answer it later through your TODOs list.

Live Collaboration

Everything is better with friends! In the DSW, multiple users can fill the DMP at the same time and see the changes made by others in real-time. Just like you would expect it in a cutting-edge online platform.

Learn more

Migrations

Life is change and we know that the specifications for your data management plan can also change at any time during the Project. In that case, with DSW there is no need to start all over again! Simply use the option of Migration and update your Project easily to a new version or even a different Knowledge Model. Moreover, when you have customization of a Knowledge Model that has been updated, you can easily migrate the customization to a newer version of the parent Knowledge Model as well.

Learn more

Version History

In DSW, every change you make in your project is saved. Furthermore, it also allows you to browse the history, watch who made changes and when, and create a version for your project's specific state. Working on the project with a group of people or having lots of changes in the project over time, the version history will definitely make your life easier!

Languages (other than English)

The Data Stewardship Wizard is provided in English by default. While we believe that in today's world, the English language is essential and accepted as the primary language for creating DMPs, it is possible to localize DSW to any other language. We run localize.ds-wizard.org, where the community can work together on different localizations, and the results are published in DSW Registry.

Funder Templates

We are working on increasing the number of Funder templates that the DSW offers, so you can easily use them while applying your project at the most common funding agencies. It takes a lot of work but we are looking forward to presenting you more funder templates soon!

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file diff --git a/contact.html b/contact.html index 1bfb2b4..3442c1c 100644 --- a/contact.html +++ b/contact.html @@ -1 +1 @@ -Contact | Data Stewardship Wizard
DSW
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DSW
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Contact

Emailinfo@ds-wizard.org
DiscordJoin our Discord
Bug reportingGitHub
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To find out more, including how to control cookies, see here: Cookie Policy
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\ No newline at end of file +Contact | Data Stewardship Wizard
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Get Started
DSW
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Contact

Emailinfo@ds-wizard.org
DiscordJoin our Discord
Bug reportingGitHub
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
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\ No newline at end of file diff --git a/cookie-policy.html b/cookie-policy.html index d4742dd..dd3eb69 100644 --- a/cookie-policy.html +++ b/cookie-policy.html @@ -1 +1 @@ -Cookie Policy | Data Stewardship Wizard
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Cookie Policy

This Cookie Policy explains how DSW ("Company", "we", "us", and "our") uses cookies and similar technologies to recognize you when you visit our website at https://ds-wizard.org, ("Website"). It explains what these technologies are and why we use them, as well as your rights to control our use of them.

In some cases we may use cookies to collect personal information, or that becomes personal information if we combine it with other information.

What are cookies?

Cookies are small data files that are placed on your computer or mobile device when you visit a website. Cookies are widely used by website owners in order to make their websites work, or to work more efficiently, as well as to provide reporting information.

Cookies set by the website owner (in this case, DSW) are called "first party cookies". Cookies set by parties other than the website owner are called "third party cookies". Third party cookies enable third party features or functionality to be provided on or through the website (e.g. analytics). The parties that set these third party cookies can recognize your computer both when it visits the website in question and also when it visits certain other websites.

Why do we use cookies?

We use first and third party cookies for several reasons. Some cookies are required for technical reasons in order for our Websites to operate, and we refer to these as "essential" or "strictly necessary" cookies. Other cookies also enable us to track and target the interests of our users to enhance the experience on our Online Properties. Third parties serve cookies through our Websites for analytics and other purposes.

How can I control cookies?

You have the right to decide whether to accept or decline cookies. You can exercise your cookie rights by setting your preferences in the Cookie Consent Manager. The Cookie Consent Manager allows you to select which categories of cookies you accept or reject. Essential cookies cannot be rejected as they are strictly necessary to provide you with services.

The Cookie Consent Manager can be found in the notification banner and on our website. If you choose to reject cookies, you may still use our website though your access to some functionality and areas of our website may be restricted. You may also set or amend your web browser controls to accept or refuse cookies. As the means by which you can refuse cookies through your web browser controls vary from browser-to-browser, you should visit your browser’s help menu for more information.

The specific types of first and third party cookies served through our Websites and the purposes they perform are described in the table below (please note that the specific cookies served may vary depending on the specific Online Properties you visit):

Analytics and customization cookies

These cookies collect information that is used either in aggregate form to help us understand how our Websites are being used, or to help us customize our Websites for you.

Name#collect
PurposeSends data such as visitor’s behavior and device to Google Analytics. It is able to keep track of the visitor across marketing channels and devices. It is a pixel tracker type cookie whose activity lasts within the browsing session.
Providertermly.io
ServiceGoogle Analytics View Service Privacy Policy
CountryUnited States
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PurposeKeeps an entry of unique ID which is then used to come up with statistical data on website usage by visitors. It is a HTTP cookie type and expires after a browsing session.
Providertermly.io
ServiceGoogle Analytics View Service Privacy Policy
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Name_ga
PurposeIt records a particular ID used to come up with data about website usage by the user. It is a HTTP cookie that expires after 2 years.
Providertermly.io
ServiceGoogle Analytics View Service Privacy Policy
CountryUnited States
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PurposeEnables Google Analytics regulate the rate of requesting. It is a HTTP cookie type that lasts for a session.
Providertermly.io
ServiceGoogle Analytics View Service Privacy Policy
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Typehttp_cookie
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Cookie Policy

This Cookie Policy explains how DSW ("Company", "we", "us", and "our") uses cookies and similar technologies to recognize you when you visit our website at https://ds-wizard.org, ("Website"). It explains what these technologies are and why we use them, as well as your rights to control our use of them.

In some cases we may use cookies to collect personal information, or that becomes personal information if we combine it with other information.

What are cookies?

Cookies are small data files that are placed on your computer or mobile device when you visit a website. Cookies are widely used by website owners in order to make their websites work, or to work more efficiently, as well as to provide reporting information.

Cookies set by the website owner (in this case, DSW) are called "first party cookies". Cookies set by parties other than the website owner are called "third party cookies". Third party cookies enable third party features or functionality to be provided on or through the website (e.g. analytics). The parties that set these third party cookies can recognize your computer both when it visits the website in question and also when it visits certain other websites.

Why do we use cookies?

We use first and third party cookies for several reasons. Some cookies are required for technical reasons in order for our Websites to operate, and we refer to these as "essential" or "strictly necessary" cookies. Other cookies also enable us to track and target the interests of our users to enhance the experience on our Online Properties. Third parties serve cookies through our Websites for analytics and other purposes.

How can I control cookies?

You have the right to decide whether to accept or decline cookies. You can exercise your cookie rights by setting your preferences in the Cookie Consent Manager. The Cookie Consent Manager allows you to select which categories of cookies you accept or reject. Essential cookies cannot be rejected as they are strictly necessary to provide you with services.

The Cookie Consent Manager can be found in the notification banner and on our website. If you choose to reject cookies, you may still use our website though your access to some functionality and areas of our website may be restricted. You may also set or amend your web browser controls to accept or refuse cookies. As the means by which you can refuse cookies through your web browser controls vary from browser-to-browser, you should visit your browser’s help menu for more information.

The specific types of first and third party cookies served through our Websites and the purposes they perform are described in the table below (please note that the specific cookies served may vary depending on the specific Online Properties you visit):

Analytics and customization cookies

These cookies collect information that is used either in aggregate form to help us understand how our Websites are being used, or to help us customize our Websites for you.

Name#collect
PurposeSends data such as visitor’s behavior and device to Google Analytics. It is able to keep track of the visitor across marketing channels and devices. It is a pixel tracker type cookie whose activity lasts within the browsing session.
Providertermly.io
ServiceGoogle Analytics View Service Privacy Policy
CountryUnited States
Typepixel_tracker
Expires insession
Name_gid
PurposeKeeps an entry of unique ID which is then used to come up with statistical data on website usage by visitors. It is a HTTP cookie type and expires after a browsing session.
Providertermly.io
ServiceGoogle Analytics View Service Privacy Policy
CountryUnited States
Typehttp_cookie
Expires in1 day
Name_ga
PurposeIt records a particular ID used to come up with data about website usage by the user. It is a HTTP cookie that expires after 2 years.
Providertermly.io
ServiceGoogle Analytics View Service Privacy Policy
CountryUnited States
Typehttp_cookie
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Name_gat#
PurposeEnables Google Analytics regulate the rate of requesting. It is a HTTP cookie type that lasts for a session.
Providertermly.io
ServiceGoogle Analytics View Service Privacy Policy
CountryUnited States
Typehttp_cookie
Expires in1 minute
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\ No newline at end of file diff --git a/data-management-plans.html b/data-management-plans.html index f25492f..38f4f86 100644 --- a/data-management-plans.html +++ b/data-management-plans.html @@ -1 +1 @@ -Data Management Plans | Data Stewardship Wizard
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Data Management Plans

DMPs as formal documents that outline how data were managed during and post-project have become an important and often indispensable part of grant applications, as well as a good research practice. DSW brings a complex solution for creating high-quality DMPs in any discipline.

Data Management Plans Illustration

Smart Questionnaires

The Data Stewardship Wizard provides a simple way to create the DMP by filling the Questionnaire in a smart way. What does "smart way" mean? Based on your previous answers in the Questionnaire, only relevant questions for your case will be shown and further followed.

Smart Questionnaires

Guidance

Our smart questionnaires will effortlessly guide you through the vast knowledge of data stewardship by asking you relevant questions, offering hints, multimedia contents, external resources and community help.

Guidance

Data Stewardship Hints

With the kind permission of the Taylor & Francis Group, we provide information and hints from Data Stewardship for Open Science by Barend Mons directly in the Data Stewardship Wizard.

Data Stewardship Hints

Project Phases

A project can have several phases - before submitting the proposal, before submitting the data management plan, and before finishing the project. These phases differ in the number and completeness of the questions answered in the project's Questionnaire. You can easily set the correct phase that responds to the phase your project is currently in.

Project Phases

Project Sharing & User Access

Share your Projects with your colleagues whether they have a DSW user account or not. Furthermore, you can set their access rights as well and let them just view, edit or even own the Project.

Project Sharing & User Access

Comments & Editor Notes

Get feedback and discuss your project. You can share it in comment mode for a review or write editor notes visible only to the project editors.

Comments & Editor Notes

Online Collaboration

You can collaborate online in real-time on your data management plans with other users or anyone who you send the link to. Just like you would expect it in a cutting-edge online platform.

Online Collaboration

Version History

Every change you make in your project is saved. You can browse the history, watch who makes changes and when, and create a version for your project's specific state.

Version History
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\ No newline at end of file +Data Management Plans | Data Stewardship Wizard
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Data Management Plans

DMPs as formal documents that outline how data were managed during and post-project have become an important and often indispensable part of grant applications, as well as a good research practice. DSW brings a complex solution for creating high-quality DMPs in any discipline.

Data Management Plans Illustration

Smart Questionnaires

The Data Stewardship Wizard provides a simple way to create the DMP by filling the Questionnaire in a smart way. What does "smart way" mean? Based on your previous answers in the Questionnaire, only relevant questions for your case will be shown and further followed.

Smart Questionnaires

Guidance

Our smart questionnaires will effortlessly guide you through the vast knowledge of data stewardship by asking you relevant questions, offering hints, multimedia contents, external resources and community help.

Guidance

Data Stewardship Hints

With the kind permission of the Taylor & Francis Group, we provide information and hints from Data Stewardship for Open Science by Barend Mons directly in the Data Stewardship Wizard.

Data Stewardship Hints

Project Phases

A project can have several phases - before submitting the proposal, before submitting the data management plan, and before finishing the project. These phases differ in the number and completeness of the questions answered in the project's Questionnaire. You can easily set the correct phase that responds to the phase your project is currently in.

Project Phases

Project Sharing & User Access

Share your Projects with your colleagues whether they have a DSW user account or not. Furthermore, you can set their access rights as well and let them just view, edit or even own the Project.

Project Sharing & User Access

Comments & Editor Notes

Get feedback and discuss your project. You can share it in comment mode for a review or write editor notes visible only to the project editors.

Comments & Editor Notes

Online Collaboration

You can collaborate online in real-time on your data management plans with other users or anyone who you send the link to. Just like you would expect it in a cutting-edge online platform.

Online Collaboration

Version History

Every change you make in your project is saved. You can browse the history, watch who makes changes and when, and create a version for your project's specific state.

Version History
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\ No newline at end of file diff --git a/data-steward.html b/data-steward.html index 7837796..7a6182f 100644 --- a/data-steward.html +++ b/data-steward.html @@ -1 +1 @@ -Data Steward | Data Stewardship Wizard
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Data Steward

Data Stewards are the experts who help researchers with managing their data and creating Data Management Plans. In DSW, they build so-called Knowledge Models and DMP Templates that researchers can use.

Data Steward Illustration

Build Knowledge Models

Knowledge Model is a tree-like structure of chapters, questions, answers, references and more that captures the knowledge of what should be considered in a DMP and the research experiment in general.

Data Stewards can adjust and extend existing Knowledge Models or build new ones from scratch.

Learn More

Integrate with External Services

It is possible to integrate questions with external resources or databases, such as FAIRsharing. Then, when researchers answer these questions, they can pick from an already existing list of answers. These answers also contain the link to the original resource.

Learn More

Incorporate FAIR metrics

Some answers are better than others. In DSW, you can indicate how each answer affects the FAIR metrics to give hints for researchers on what to improve.

Learn More

Publish for Use

When the Knowledge Model is ready to be used by researchers, you need to publish it first. This step involves assigning additional metadata such as a license or version number. Once the version is published, it is persistent and cannot be changed. You can always create a new version whenever you need though.

Create DMP Templates

Knowledge Models define how to capture the information needed, but they are not the Data Management Plan yet. For that, we use DMP Templates. One Knowledge Model can use multiple DMP templates. The idea is simple: answer once, get DMPs in any form needed, whether it is a document following Science Europe recommendations or a machine-actionable DMP.

Data Stewards can use DSW Template Development Kit to build DMP Templates.

Learn More

DSW Registry

DSW Registry is a place where we share Knowledge Models and DMP Templates created by us. You can easily import them into a DSW instance and use them straight away or extend and modify them further to fit your needs.

Explore DSW Registry

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\ No newline at end of file +Data Steward | Data Stewardship Wizard
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Data Steward

Data Stewards are the experts who help researchers with managing their data and creating Data Management Plans. In DSW, they build so-called Knowledge Models and DMP Templates that researchers can use.

Data Steward Illustration

Build Knowledge Models

Knowledge Model is a tree-like structure of chapters, questions, answers, references and more that captures the knowledge of what should be considered in a DMP and the research experiment in general.

Data Stewards can adjust and extend existing Knowledge Models or build new ones from scratch.

Learn More

Integrate with External Services

It is possible to integrate questions with external resources or databases, such as FAIRsharing. Then, when researchers answer these questions, they can pick from an already existing list of answers. These answers also contain the link to the original resource.

Learn More

Incorporate FAIR metrics

Some answers are better than others. In DSW, you can indicate how each answer affects the FAIR metrics to give hints for researchers on what to improve.

Learn More

Publish for Use

When the Knowledge Model is ready to be used by researchers, you need to publish it first. This step involves assigning additional metadata such as a license or version number. Once the version is published, it is persistent and cannot be changed. You can always create a new version whenever you need though.

Create DMP Templates

Knowledge Models define how to capture the information needed, but they are not the Data Management Plan yet. For that, we use DMP Templates. One Knowledge Model can use multiple DMP templates. The idea is simple: answer once, get DMPs in any form needed, whether it is a document following Science Europe recommendations or a machine-actionable DMP.

Data Stewards can use DSW Template Development Kit to build DMP Templates.

Learn More

DSW Registry

DSW Registry is a place where we share Knowledge Models and DMP Templates created by us. You can easily import them into a DSW instance and use them straight away or extend and modify them further to fit your needs.

Explore DSW Registry

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
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\ No newline at end of file diff --git a/data-stewardship.html b/data-stewardship.html index e38d929..fcd1ea9 100644 --- a/data-stewardship.html +++ b/data-stewardship.html @@ -1 +1 @@ -Data Stewardship | Data Stewardship Wizard
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Data Stewardship

Data stewardship focuses on tactical coordination and implementation responsible for establishing data-quality metrics and other requirements regarding good data management. The ultimate goal is to provide high-quality data that is easily accessible in a consistent manner.

Data Stewardship Illustration

Who Should Practice Data Stewardship?

Everyone who collects, views, stores, exchanges, aggregates, analyzes, and / or uses electronic data should practice data stewardship.

How Is Data Stewardship Done?

Data stewardship is a very complex discipline responsible mainly for defining the data, creating processes and procedures, maintaining the quality of the data, optimizing workflows, monitoring data usage to assist teams, ensuring compliance and security of the data.

How DSW Helps?

Does data stewardship sound complicated? The Data Stewardship Wizard will effortlessly guide you through the creation of your data management plan by e.g. giving you hints about good data management practice, checking the FAIRness of your plan, or asking and following only questions relevant to your project.

Learn More About Data Stewardship

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\ No newline at end of file +Data Stewardship | Data Stewardship Wizard
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Data Stewardship

Data stewardship focuses on tactical coordination and implementation responsible for establishing data-quality metrics and other requirements regarding good data management. The ultimate goal is to provide high-quality data that is easily accessible in a consistent manner.

Data Stewardship Illustration

Who Should Practice Data Stewardship?

Everyone who collects, views, stores, exchanges, aggregates, analyzes, and / or uses electronic data should practice data stewardship.

How Is Data Stewardship Done?

Data stewardship is a very complex discipline responsible mainly for defining the data, creating processes and procedures, maintaining the quality of the data, optimizing workflows, monitoring data usage to assist teams, ensuring compliance and security of the data.

How DSW Helps?

Does data stewardship sound complicated? The Data Stewardship Wizard will effortlessly guide you through the creation of your data management plan by e.g. giving you hints about good data management practice, checking the FAIRness of your plan, or asking and following only questions relevant to your project.

Learn More About Data Stewardship

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
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\ No newline at end of file diff --git a/dmponline-alternative.html b/dmponline-alternative.html index 66707fd..2e3b71a 100644 --- a/dmponline-alternative.html +++ b/dmponline-alternative.html @@ -1 +1 @@ -DMPonline Alternative | Data Stewardship Wizard
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DMPonline Alternative

DMPonline is another favourite tool for DM Planning. If you have some experience with it, the information here may help you start with DSW.

Man choosing between DSW and DMPonline

Knowledge Models

We have a different approach than DMPonline. In DSW, you do not choose a template according to your funder for your plan, you choose a Knowledge model. A Knowledge model is similar to a template as you know it because it determines the questions asked. However, the "Common DSW Knowledge Model" focuses on asking all questions important for your project and providing guidance. The questions are asked in a tree-like structure with a lot of advice and tips. They can also help you make your data FAIR and machine-actionable without the need of being an expert on these topics.

Learn more
Knowledge Models

Different Templates

We also have document templates in DSW, they are used when you need to download or submit your plan. The template selects only the questions and answers required by it. That way, if your funder requires a specific template, you can submit the plan according to their needs, but still have all the questions and answers that are important for you and your project. You can use several templates over time for one plan. You are not limited to use only one and having to create different plans for different templates.

Learn more
Different Templates

Projects

To create a plan, sign in DSW and choose Projects on the left upper side of the main page. Then click on the "Create" button and you can create your new Project. Now you only enter the name of your project and the knowledge model and you can start writing your new plan.

Learn more
Projects

Other Features

Our other features such as TODOs, version history, and live collaboration will surely help you make your plans better, more beneficial, and easier to write!

Learn more
Other Features
DSW Compared to Other DMP Tools
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\ No newline at end of file +DMPonline Alternative | Data Stewardship Wizard
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DMPonline Alternative

DMPonline is another favourite tool for DM Planning. If you have some experience with it, the information here may help you start with DSW.

Man choosing between DSW and DMPonline

Knowledge Models

We have a different approach than DMPonline. In DSW, you do not choose a template according to your funder for your plan, you choose a Knowledge model. A Knowledge model is similar to a template as you know it because it determines the questions asked. However, the "Common DSW Knowledge Model" focuses on asking all questions important for your project and providing guidance. The questions are asked in a tree-like structure with a lot of advice and tips. They can also help you make your data FAIR and machine-actionable without the need of being an expert on these topics.

Learn more
Knowledge Models

Different Templates

We also have document templates in DSW, they are used when you need to download or submit your plan. The template selects only the questions and answers required by it. That way, if your funder requires a specific template, you can submit the plan according to their needs, but still have all the questions and answers that are important for you and your project. You can use several templates over time for one plan. You are not limited to use only one and having to create different plans for different templates.

Learn more
Different Templates

Projects

To create a plan, sign in DSW and choose Projects on the left upper side of the main page. Then click on the "Create" button and you can create your new Project. Now you only enter the name of your project and the knowledge model and you can start writing your new plan.

Learn more
Projects

Other Features

Our other features such as TODOs, version history, and live collaboration will surely help you make your plans better, more beneficial, and easier to write!

Learn more
Other Features
DSW Compared to Other DMP Tools
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\ No newline at end of file diff --git a/document-templates.html b/document-templates.html index de16b31..f09d15d 100644 --- a/document-templates.html +++ b/document-templates.html @@ -1 +1 @@ -Document Templates | Data Stewardship Wizard
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Document Templates

In the Data Stewardship Wizard, a document template describes how the replies from a questionnaire are composed into a document. This allows to produce various kinds of documents from a single questionnaire by using different templates.

Document Templates Illustration

Ready to Use Templates

There are several templates available in DSW Registry. The Questionnaire Report template can be used in any project, and it follows the structure of the questionnaire. Then, there are also funder-specific templates: Horizon Europe, Horizon 2020, and Science Europe DMP templates. These follow the structure expected by a funder and can serve for project applications.

Finally, there is the Machine-Actionable DMP (maDMP) template according to the RDA DMP Common Standard. It is suitable for further processing in other tools as it is compliant with the JSON schema provided by the recommendations.

Ready to Use Templates

File Formats

Each template can specify the number of formats that can be used for export. For example, the Questionnaire Report, as well as Horizon Europe, Horizon 2020, and Science Europe templates, can be exported as HTML, a Word document, LaTeX, Markdown, an OpenDocument, or a PDF. Similarly, the Machine-Actionable DMP can be exported into JSON but also into various RDF formats such as RDF/XML, Turtle, TRiG, or JSON-LD.

File Formats

Custom Template

Anyone can develop a custom template that transforms replies in a questionnaire (knowledge model) in any way. There is no limitation whatsoever; any textual representation can be created by using the well-known Jinja2 templating markup language. It requires basic programming skills (variables, conditions, loops); however, training materials are provided.

Having a custom template may be helpful for various use cases. For example, one may need to submit a DMP to a different funder that requires the following own DMP template. Organization management may want to have a unique project summary with essential information and FAIR metrics on a single page. A data steward may need a mind map visualization of a knowledge model.

Custom Template

Document Template Editor

The Document Template editor is a tool for creating new document templates or adjusting the existing ones to your needs. You can write the templates directly in DSW and preview them on your projects immediately.

Document Template Editor

Template Development Kit

Alternatively, you can use the Template Development Kit (TDK). It is a convenient command-line tool for managing template projects. First, it helps to create a new template or download existing ones from a DSW instance. Then, it can be used to upload a template to a DSW instance, validate it, or create a ZIP package that is importable through the DSW user interface.

The recommendations and other hints on how to develop a template are part of the technical documentation. Finally, there is also a video recording of a TDK tutorial.

Template Development Kit
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Document Templates

In the Data Stewardship Wizard, a document template describes how the replies from a questionnaire are composed into a document. This allows to produce various kinds of documents from a single questionnaire by using different templates.

Document Templates Illustration

Ready to Use Templates

There are several templates available in DSW Registry. The Questionnaire Report template can be used in any project, and it follows the structure of the questionnaire. Then, there are also funder-specific templates: Horizon Europe, Horizon 2020, and Science Europe DMP templates. These follow the structure expected by a funder and can serve for project applications.

Finally, there is the Machine-Actionable DMP (maDMP) template according to the RDA DMP Common Standard. It is suitable for further processing in other tools as it is compliant with the JSON schema provided by the recommendations.

Ready to Use Templates

File Formats

Each template can specify the number of formats that can be used for export. For example, the Questionnaire Report, as well as Horizon Europe, Horizon 2020, and Science Europe templates, can be exported as HTML, a Word document, LaTeX, Markdown, an OpenDocument, or a PDF. Similarly, the Machine-Actionable DMP can be exported into JSON but also into various RDF formats such as RDF/XML, Turtle, TRiG, or JSON-LD.

File Formats

Custom Template

Anyone can develop a custom template that transforms replies in a questionnaire (knowledge model) in any way. There is no limitation whatsoever; any textual representation can be created by using the well-known Jinja2 templating markup language. It requires basic programming skills (variables, conditions, loops); however, training materials are provided.

Having a custom template may be helpful for various use cases. For example, one may need to submit a DMP to a different funder that requires the following own DMP template. Organization management may want to have a unique project summary with essential information and FAIR metrics on a single page. A data steward may need a mind map visualization of a knowledge model.

Custom Template

Document Template Editor

The Document Template editor is a tool for creating new document templates or adjusting the existing ones to your needs. You can write the templates directly in DSW and preview them on your projects immediately.

Document Template Editor

Template Development Kit

Alternatively, you can use the Template Development Kit (TDK). It is a convenient command-line tool for managing template projects. First, it helps to create a new template or download existing ones from a DSW instance. Then, it can be used to upload a template to a DSW instance, validate it, or create a ZIP package that is importable through the DSW user interface.

The recommendations and other hints on how to develop a template are part of the technical documentation. Finally, there is also a video recording of a TDK tutorial.

Template Development Kit
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\ No newline at end of file diff --git a/dsw-story.html b/dsw-story.html index 3a96992..629f38c 100644 --- a/dsw-story.html +++ b/dsw-story.html @@ -1 +1 @@ -The DSW Story | Data Stewardship Wizard
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The DSW Story

The DSW story originates in the Netherlands where Dr Rob Hooft of the Dutch Techcentre for Lifesciences (DTL) started collecting knowledge about data stewardship around 2012, when taking part in discussions on the introduction of Data Management Plans by national funder ZonMw, and formalised it in the form of a hierarchical mind map. After collecting information at lectures and from discussions for some time, the mind map grew to over 600 items and was almost as tall as Rob when printed out for an ELIXIR meeting. This was when Dr Hooft started thinking about programming a tool for navigating through the map.

In the Spring of 2015, Dr Robert Pergl from the Faculty of Information Technology of Czech Technical University (CTU) in Prague, Czech Republic, started working on dynamic web forms systems. CTU had freshly joined ELIXIR CZ infrastructure at that time, and together with the Head of Node, Dr Jiří Vondrášek, Dr Pačes, and Dr Pergl opened the topic of data management. The dynamic web forms system was developed to make a user-friendly questionnaire to gather information about data management practices in ELIXIR CZ.

Robert Pergl and Jiří Vondrášek
Robert Pergl and Jiří Vondrášek

The key moment when the DSW idea was conceived was when these two roads met in the Autumn of 2015, at the ELIXIR CZ meeting, where Dr Pergl presented his work. Dr Hooft was present, as was a FAIR visionary prof. Barend Mons of Leiden University Medical Centre, at that time ELIXIR NL Head of Node, who said, "Rob has this brilliant mind map, and you have such a nice questionnaire tool, why don't you put it together?" And so they did. In the Autumn of 2016, the first version of The Data Stewardship Wizard was released, effectively bringing the mind map knowledge in the form of an interactive questionnaire with hints, follow-up questions, additional links to resources and experts in the field, and it started to get attention and feedback from the future user community.

Barend Mons, Robert Pergl and Marek Suchánek
Barend Mons, Robert Pergl and Marek Suchánek

Dr Pergl was then joined in his efforts by his students, a doctoral candidate Marek Suchánek, MSc, and master students Vojtěch Knaisl and Jan Slifka. They started improving the DSW prototype, and in 2018, an entirely rewritten production-ready version of DSW was released. Since then, DSW grew to a professional-grade rock-solid software tool built on cutting-edge software technologies with regular releases bringing an ever-growing set of features requested by its community.

Rob Hooft, Vojtěch Knaisl and Marek Suchánek
Rob Hooft, Vojtěch Knaisl and Marek Suchánek

The uniqueness of DSW lies in the combination of skillfully crafted software and its valuable contents – the Knowledge Model encompassing the data stewardship domain. It represents a tool that gives guidance, decision support, and learning – the learning aspect was strongly increased by organically linking parts of the book by prof. Barend Mons, Data Stewardship for Open Science in 2018, which structure follows the mind map.

Clearly, the success of DSW has been achieved not only by the quality of software and its unique content but also thanks to the support of ELIXIR CZ and ELIXIR NL. Over time, other ELIXIR nodes started contributing, and a very nice and active community started forming, resulting in the embedding of DSW as "The ELIXIR data management tool".

ELIXIR All Hands 2019
ELIXIR All Hands 2019

The impact of DSW goes beyond life science and ELIXIR with the strong presence in the efforts and projects of the GO FAIR initiative and the GO FAIR Foundation. Apart from being a tool helping to make the research results FAIR as part of good data stewardship, the DSW proved to be a versatile technology – the so-called FIP Wizard became a part of the Three-point FAIRification Framework of GO FAIR, a solution "How to GO FAIR" and its engine were used in the VODAN-in-a-box project in 2020, a solution for gathering and storing FAIR COVID data.

DSW is also a key component of the EU project "ELIXIR CONVERGE", a 3-year project from 2020-2023, in which all the ELIXIR nodes participate. In ELIXIR CONVERGE, DSW interacts with RDMkit: creating mutual references, and that way presenting research data management knowledge to different audiences together. DSW's knowledge model also benefits from the experience brought together in ELIXIR CONVERGE.

DSW became strongly community-driven in 2020. Dr Jana Freeman joined the Czech team as the Community Manager and started her excellent job of handling communications, social media, organising events, and also doing training and managing the user documentation. After a few months, she was reinforced by Tereza Machačová in the role of an intern. To steer the development of DSW also "from the top", the Advisory Board was founded in the Autumn of the same year. It is formed by the representatives of major adopters of DSW.

DSW team at teambuilding hike
DSW team at teambuilding hike

A quality of a tool is not only given by the quality of its make but very much by quality-in-use. At DSW, we are very much aware that good training is very important to get our users at peak effectiveness in data management planning. This is why we regularly organise training on features and topics. Even more important in this respect are training organised by various ELIXIR nodes that are more focused on specific use cases and scenarios of users.

Funding by sponsors ELIXIR, ELIXIR CZ and the Ministry of Education, Youth and Sports of the Czech Republic provides sustainable operation and development of an open-source, free version of DSW operated on CESNET infrastructure. To satisfy the high demands of industry and practice, the Codevence company was founded by the team in 2020 to offer professional custom-tailored services for commercial companies.

Today, DSW is used by thousands of users from many universities, organisations, and several major commercial companies. You may like to read some of the success stories, and you may find a lot of interesting and useful information on our web pages and please do not hesitate to contact us!

We wish you many magical moments with the Data Stewardship Wizard, and we hope you enjoy its use as much as we enjoy working on it!

The DSW team

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\ No newline at end of file +The DSW Story | Data Stewardship Wizard
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The DSW Story

The DSW story originates in the Netherlands where Dr Rob Hooft of the Dutch Techcentre for Lifesciences (DTL) started collecting knowledge about data stewardship around 2012, when taking part in discussions on the introduction of Data Management Plans by national funder ZonMw, and formalised it in the form of a hierarchical mind map. After collecting information at lectures and from discussions for some time, the mind map grew to over 600 items and was almost as tall as Rob when printed out for an ELIXIR meeting. This was when Dr Hooft started thinking about programming a tool for navigating through the map.

In the Spring of 2015, Dr Robert Pergl from the Faculty of Information Technology of Czech Technical University (CTU) in Prague, Czech Republic, started working on dynamic web forms systems. CTU had freshly joined ELIXIR CZ infrastructure at that time, and together with the Head of Node, Dr Jiří Vondrášek, Dr Pačes, and Dr Pergl opened the topic of data management. The dynamic web forms system was developed to make a user-friendly questionnaire to gather information about data management practices in ELIXIR CZ.

Robert Pergl and Jiří Vondrášek
Robert Pergl and Jiří Vondrášek

The key moment when the DSW idea was conceived was when these two roads met in the Autumn of 2015, at the ELIXIR CZ meeting, where Dr Pergl presented his work. Dr Hooft was present, as was a FAIR visionary prof. Barend Mons of Leiden University Medical Centre, at that time ELIXIR NL Head of Node, who said, "Rob has this brilliant mind map, and you have such a nice questionnaire tool, why don't you put it together?" And so they did. In the Autumn of 2016, the first version of The Data Stewardship Wizard was released, effectively bringing the mind map knowledge in the form of an interactive questionnaire with hints, follow-up questions, additional links to resources and experts in the field, and it started to get attention and feedback from the future user community.

Barend Mons, Robert Pergl and Marek Suchánek
Barend Mons, Robert Pergl and Marek Suchánek

Dr Pergl was then joined in his efforts by his students, a doctoral candidate Marek Suchánek, MSc, and master students Vojtěch Knaisl and Jan Slifka. They started improving the DSW prototype, and in 2018, an entirely rewritten production-ready version of DSW was released. Since then, DSW grew to a professional-grade rock-solid software tool built on cutting-edge software technologies with regular releases bringing an ever-growing set of features requested by its community.

Rob Hooft, Vojtěch Knaisl and Marek Suchánek
Rob Hooft, Vojtěch Knaisl and Marek Suchánek

The uniqueness of DSW lies in the combination of skillfully crafted software and its valuable contents – the Knowledge Model encompassing the data stewardship domain. It represents a tool that gives guidance, decision support, and learning – the learning aspect was strongly increased by organically linking parts of the book by prof. Barend Mons, Data Stewardship for Open Science in 2018, which structure follows the mind map.

Clearly, the success of DSW has been achieved not only by the quality of software and its unique content but also thanks to the support of ELIXIR CZ and ELIXIR NL. Over time, other ELIXIR nodes started contributing, and a very nice and active community started forming, resulting in the embedding of DSW as "The ELIXIR data management tool".

ELIXIR All Hands 2019
ELIXIR All Hands 2019

The impact of DSW goes beyond life science and ELIXIR with the strong presence in the efforts and projects of the GO FAIR initiative and the GO FAIR Foundation. Apart from being a tool helping to make the research results FAIR as part of good data stewardship, the DSW proved to be a versatile technology – the so-called FIP Wizard became a part of the Three-point FAIRification Framework of GO FAIR, a solution "How to GO FAIR" and its engine were used in the VODAN-in-a-box project in 2020, a solution for gathering and storing FAIR COVID data.

DSW is also a key component of the EU project "ELIXIR CONVERGE", a 3-year project from 2020-2023, in which all the ELIXIR nodes participate. In ELIXIR CONVERGE, DSW interacts with RDMkit: creating mutual references, and that way presenting research data management knowledge to different audiences together. DSW's knowledge model also benefits from the experience brought together in ELIXIR CONVERGE.

DSW became strongly community-driven in 2020. Dr Jana Freeman joined the Czech team as the Community Manager and started her excellent job of handling communications, social media, organising events, and also doing training and managing the user documentation. After a few months, she was reinforced by Tereza Machačová in the role of an intern. To steer the development of DSW also "from the top", the Advisory Board was founded in the Autumn of the same year. It is formed by the representatives of major adopters of DSW.

DSW team at teambuilding hike
DSW team at teambuilding hike

A quality of a tool is not only given by the quality of its make but very much by quality-in-use. At DSW, we are very much aware that good training is very important to get our users at peak effectiveness in data management planning. This is why we regularly organise training on features and topics. Even more important in this respect are training organised by various ELIXIR nodes that are more focused on specific use cases and scenarios of users.

Funding by sponsors ELIXIR, ELIXIR CZ and the Ministry of Education, Youth and Sports of the Czech Republic provides sustainable operation and development of an open-source, free version of DSW operated on CESNET infrastructure. To satisfy the high demands of industry and practice, the Codevence company was founded by the team in 2020 to offer professional custom-tailored services for commercial companies.

Today, DSW is used by thousands of users from many universities, organisations, and several major commercial companies. You may like to read some of the success stories, and you may find a lot of interesting and useful information on our web pages and please do not hesitate to contact us!

We wish you many magical moments with the Data Stewardship Wizard, and we hope you enjoy its use as much as we enjoy working on it!

The DSW team

Get Started

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\ No newline at end of file diff --git a/elixir-norway-dsw-story.html b/elixir-norway-dsw-story.html index 614981c..a5b9fc1 100644 --- a/elixir-norway-dsw-story.html +++ b/elixir-norway-dsw-story.html @@ -1 +1 @@ -The ELIXIR Norway DS Wizard Story | Data Stewardship Wizard
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The ELIXIR Norway DS Wizard Story

Norwegian funders require that research groups submit data management plans (DMPs) upon signing the contract for their research projects. Generating a DMP has been regarded by many researchers as a mere administrative burden, rather than a tool to revise their habits and support their projects.

ELIXIR Norway, in collaboration with the Centre for Digital Life Norway, has explored methods to support Norwegian researchers in data management planning for several years. After we got to know the Data Steward Wizard (DSW) in 2018, we started to use it fully in production in 2019 to enable assisted data management planning (DMP) for Life-Scientists across Norway. We operate several instances for our own testing and use one instance hosted by ELIXIR-CZ for us for production.

The DSW provides us with the unique opportunity to facilitate both the generation of DMPs by the research community and at the same time to increase awareness for research data management. We have adapted the Data Steward Wizard Life-Science knowledge model (KM) for users in Norway, and included additional guidance on Norwegian infrastructures, requirements for sensitive data, local policies and regulations. This knowledge model has been an eye-opener to research projects in all stages and simultaneously guides the users to practical solutions for all aspects of data handling, including allocating resources for the necessary data analysis and storage infrastructure.

NeLS toolkit
The Norwegian e-Infrastructure for Life Sciences (NeLS) Data Management tool assembly. Learn more.

We were very happy when DSW reached full compliance with the Science Europe guidelines through work performed at the Biohackathon 2019, as these guidelines are used by the major funders in Norway.

The DSW has been very valuable for several of our DM-training events across Norwegian Universities. This is also facilitated by the fact that users can authenticate with their national FEIDE credentials.

Our users report in person and through the inbuilt feedback mechanism that these aspects have helped them to think in new terms about research data management and to directly address practical challenges. The hierarchical format of the questionnaires and the integration of key resources like FAIRsharing and bio.tools into DSW have also proved very helpful for our users.

DSW is a cornerstone for us in our new BioMedData project in which we will, together with the other major Norwegian Life-Science research infrastructures, develop routines for FAIR end-to-end data management routines. In the near future we hope to make use of the machine actionable DMP features to provide a seamless experience for researchers who also use resources from EOSC-Nordic. We are also exploring if the DSW API can be used for direct interaction with our storage platform NeLS.

Korbinian Bösl, ELIXIR-Norway, Centre for Digital Life Norway, University of Bergen
Erik Hjerde, ELIXIR-Norway, University of Tromsø
Ståle Nygård, Training coordinator ELIXIR-Norway, University of Oslo
Thu-Hien To, ELIXIR-Norway, Norwegian University of Life Sciences
Kjersti Rise, ELIXIR-Norway, Norwegian University of Science and Technology

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The ELIXIR Norway DS Wizard Story

Norwegian funders require that research groups submit data management plans (DMPs) upon signing the contract for their research projects. Generating a DMP has been regarded by many researchers as a mere administrative burden, rather than a tool to revise their habits and support their projects.

ELIXIR Norway, in collaboration with the Centre for Digital Life Norway, has explored methods to support Norwegian researchers in data management planning for several years. After we got to know the Data Steward Wizard (DSW) in 2018, we started to use it fully in production in 2019 to enable assisted data management planning (DMP) for Life-Scientists across Norway. We operate several instances for our own testing and use one instance hosted by ELIXIR-CZ for us for production.

The DSW provides us with the unique opportunity to facilitate both the generation of DMPs by the research community and at the same time to increase awareness for research data management. We have adapted the Data Steward Wizard Life-Science knowledge model (KM) for users in Norway, and included additional guidance on Norwegian infrastructures, requirements for sensitive data, local policies and regulations. This knowledge model has been an eye-opener to research projects in all stages and simultaneously guides the users to practical solutions for all aspects of data handling, including allocating resources for the necessary data analysis and storage infrastructure.

NeLS toolkit
The Norwegian e-Infrastructure for Life Sciences (NeLS) Data Management tool assembly. Learn more.

We were very happy when DSW reached full compliance with the Science Europe guidelines through work performed at the Biohackathon 2019, as these guidelines are used by the major funders in Norway.

The DSW has been very valuable for several of our DM-training events across Norwegian Universities. This is also facilitated by the fact that users can authenticate with their national FEIDE credentials.

Our users report in person and through the inbuilt feedback mechanism that these aspects have helped them to think in new terms about research data management and to directly address practical challenges. The hierarchical format of the questionnaires and the integration of key resources like FAIRsharing and bio.tools into DSW have also proved very helpful for our users.

DSW is a cornerstone for us in our new BioMedData project in which we will, together with the other major Norwegian Life-Science research infrastructures, develop routines for FAIR end-to-end data management routines. In the near future we hope to make use of the machine actionable DMP features to provide a seamless experience for researchers who also use resources from EOSC-Nordic. We are also exploring if the DSW API can be used for direct interaction with our storage platform NeLS.

Korbinian Bösl, ELIXIR-Norway, Centre for Digital Life Norway, University of Bergen
Erik Hjerde, ELIXIR-Norway, University of Tromsø
Ståle Nygård, Training coordinator ELIXIR-Norway, University of Oslo
Thu-Hien To, ELIXIR-Norway, Norwegian University of Life Sciences
Kjersti Rise, ELIXIR-Norway, Norwegian University of Science and Technology

ELIXIR Norway logo
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\ No newline at end of file diff --git a/enabling-seamless-dmp-within-panocs.html b/enabling-seamless-dmp-within-panocs.html index 335de38..239222a 100644 --- a/enabling-seamless-dmp-within-panocs.html +++ b/enabling-seamless-dmp-within-panocs.html @@ -1 +1 @@ -Enabling Seamless Data Management Planning within PaNOSC with DSW | Data Stewardship Wizard
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Enabling Seamless Data Management Planning within PaNOSC

The Photon and Neutron Open Science Cloud (PaNOSC) project is a beacon of collaboration and innovation in the realm of scientific research infrastructure. Comprising various individual Research Infrastructures (RIs) including CERIC-ERIC, ELI-ERIC, ESRF, ESS, EuXFEL, and ILL, PaNOSC embarked on a mission to enhance the management of research data across multiple domains. The common goal shared by these RIs was to revolutionize Data Management Planning (DMP) for the benefit of both researchers and facilities.

In their quest for an effective DMP solution [1], the PaNOSC project members recognized the need for a tool that could not only harmonize the DMP process across their diverse RIs but also seamlessly integrate within each facility's IT environment. The solution they discovered and adopted was the Data Stewardship Wizard (DSW). The choice of DSW was driven by its unparalleled flexibility, powerful Knowledge Model (KM) approach, ease of installation, and unwavering support from its developers.

DSW proved to be a suitable platform for PaNOSC, enabling them to standardize DMPs across the entire project while still accommodating the unique requirements of each facility. The implementation of DMPs using DSW provided PaNOSC facilities with several key advantages:

  • Efficiency: DSW pre-filled a substantial portion of DMPs, allowing facilities to save time and effort in DMP creation. The ESFR, for instance, succeeded in generating over 1150 DMPs, with approximately 60% of the content being auto-populated, signifying a significant leap in efficiency.
  • Clarity for Users: DMPs offer researchers a clear understanding of what to expect from the facility, the data they will produce, and the tools available for data management. This clarity empowers users to navigate their research projects more effectively.
  • Information Gathering: Facilities gained valuable insights into user needs for data management and processing, enabling them to plan resources more effectively.

The implementation of DMPs and DSW has yielded remarkable outcomes. First of all, the establishment of a common DMP template has enhanced interoperability across facilities. Additionally, the development of a universal software for populating DSW facilitates seamless integration into RI's IT infrastructure. The ESRF stands out as a notable example, successfully implementing this integration. Other facilities are also reaping the benefits of streamlined DMP processes, even if some of them are still in the early stages of implementation.

DSW in ESRF Architecture.
Architecture and DMP data flow at the ESRF [1].

Looking ahead, there is an exciting future for DMPs and DSW with use of outputs and experience from the PaNOSC project for making data FAIRer [2] for the Photon and Neutron communities of Europe. The creation of community-specific templates to automatically generate DMPs for scientific projects is on the horizon. DMPs will evolve into machine-readable documents, facilitating the optimal exploitation of their content and supporting a broad range of applications. While some facilities have already made DMPs a mandatory step in their proposal workflows, others are considering the same, ensuring that DMPs will play an increasingly central role in the research process. DMPs will be used as a standard way of gathering information for building knowledge graphs in the new EU project OSTrails.

In summary, the PaNOSC project's journey with DSW is a testament to the transformative power of collaboration and the effectiveness through machine-actionability of modern tools in research data management. With DSW, the project has not only streamlined data management but also laid the foundation for a future where research data is efficiently harnessed to advance science.

Marjolaine Bodin, European Synchrotron Radiation Facility (ESRF)

References

  1. Bodin, M., Bolmsten, F., Aulin, P., Ivănoaica, T., Olivo, A., Malka, J., Wrona, K. and Götz, A., 2023. Data Management Plans for the Photon and Neutron Communities. Data Science Journal, 22(1), p.30. DOI: https://doi.org/10.5334/dsj-2023-030.
  2. Götz, A., 2023. Data Management Plans as a Tool for Making Data FAIR. Open Access Government, October 2023, p.246-247. DOI: https://doi.org/10.56367/OAG-040-10749.
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Enabling Seamless Data Management Planning within PaNOSC

The Photon and Neutron Open Science Cloud (PaNOSC) project is a beacon of collaboration and innovation in the realm of scientific research infrastructure. Comprising various individual Research Infrastructures (RIs) including CERIC-ERIC, ELI-ERIC, ESRF, ESS, EuXFEL, and ILL, PaNOSC embarked on a mission to enhance the management of research data across multiple domains. The common goal shared by these RIs was to revolutionize Data Management Planning (DMP) for the benefit of both researchers and facilities.

In their quest for an effective DMP solution [1], the PaNOSC project members recognized the need for a tool that could not only harmonize the DMP process across their diverse RIs but also seamlessly integrate within each facility's IT environment. The solution they discovered and adopted was the Data Stewardship Wizard (DSW). The choice of DSW was driven by its unparalleled flexibility, powerful Knowledge Model (KM) approach, ease of installation, and unwavering support from its developers.

DSW proved to be a suitable platform for PaNOSC, enabling them to standardize DMPs across the entire project while still accommodating the unique requirements of each facility. The implementation of DMPs using DSW provided PaNOSC facilities with several key advantages:

  • Efficiency: DSW pre-filled a substantial portion of DMPs, allowing facilities to save time and effort in DMP creation. The ESFR, for instance, succeeded in generating over 1150 DMPs, with approximately 60% of the content being auto-populated, signifying a significant leap in efficiency.
  • Clarity for Users: DMPs offer researchers a clear understanding of what to expect from the facility, the data they will produce, and the tools available for data management. This clarity empowers users to navigate their research projects more effectively.
  • Information Gathering: Facilities gained valuable insights into user needs for data management and processing, enabling them to plan resources more effectively.

The implementation of DMPs and DSW has yielded remarkable outcomes. First of all, the establishment of a common DMP template has enhanced interoperability across facilities. Additionally, the development of a universal software for populating DSW facilitates seamless integration into RI's IT infrastructure. The ESRF stands out as a notable example, successfully implementing this integration. Other facilities are also reaping the benefits of streamlined DMP processes, even if some of them are still in the early stages of implementation.

DSW in ESRF Architecture.
Architecture and DMP data flow at the ESRF [1].

Looking ahead, there is an exciting future for DMPs and DSW with use of outputs and experience from the PaNOSC project for making data FAIRer [2] for the Photon and Neutron communities of Europe. The creation of community-specific templates to automatically generate DMPs for scientific projects is on the horizon. DMPs will evolve into machine-readable documents, facilitating the optimal exploitation of their content and supporting a broad range of applications. While some facilities have already made DMPs a mandatory step in their proposal workflows, others are considering the same, ensuring that DMPs will play an increasingly central role in the research process. DMPs will be used as a standard way of gathering information for building knowledge graphs in the new EU project OSTrails.

In summary, the PaNOSC project's journey with DSW is a testament to the transformative power of collaboration and the effectiveness through machine-actionability of modern tools in research data management. With DSW, the project has not only streamlined data management but also laid the foundation for a future where research data is efficiently harnessed to advance science.

Marjolaine Bodin, European Synchrotron Radiation Facility (ESRF)

References

  1. Bodin, M., Bolmsten, F., Aulin, P., Ivănoaica, T., Olivo, A., Malka, J., Wrona, K. and Götz, A., 2023. Data Management Plans for the Photon and Neutron Communities. Data Science Journal, 22(1), p.30. DOI: https://doi.org/10.5334/dsj-2023-030.
  2. Götz, A., 2023. Data Management Plans as a Tool for Making Data FAIR. Open Access Government, October 2023, p.246-247. DOI: https://doi.org/10.56367/OAG-040-10749.
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\ No newline at end of file diff --git a/enterprise.html b/enterprise.html index eeb070d..ca3b618 100644 --- a/enterprise.html +++ b/enterprise.html @@ -1 +1 @@ -Enterprise | Data Stewardship Wizard
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Enterprise

Thorough data management planning is crucial for research in the enterprise environment. The Data Stewardship Wizard educates its users and helps plan management of data, the precious results of projects.

Enterprise Illustration

Prepare the Content

First, it is necessary to specify what researchers must provide information to plan data management in the organization properly. As each enterprise organization is unique, the way of planning may be more or less different. The Data Stewardship Wizard is ready for that and allows to create knowledge models from scratch and customize existing ones.

Then the replies to a questionnaire specified by the knowledge model may be transformed into different forms suitable for evaluation or other internal/external purposes. By having a custom export template(s), researchers will be able to efficiently provide reports for their projects, just as DMPs for funding agencies.

Learn More

Adjust Look and Feel

Keeping consistent design and branding across information systems is essential in a business environment. DSW can be tailored to use corporate logos, colours, and fonts. Other UI and UX adjustments are also possible using custom stylesheets.

It is possible to also use the same design for exported documents, so all the PDFs from DSW have the colours, fonts, and logo in the header, just as the company's graphic handbook dictates.

Integrate in Workflows and Systems

The Data Stewardship Wizard provides an API that can be used for automation and integration. Hence, other systems in the environment can query and manipulate the content in DSW. For example, whenever a new project is created in the local project management system, a related project is prepared in DSW for specific employees.

Furthermore, DSW can also consume other services such as local SSO, document management systems and databases, controlled vocabularies and repositories with APIs. Thus, the Data Stewardship Wizard can be easily be plugged into the enterprise environment and become part of everyday workflows.

Learn More

Evaluate and Improve

By planning data management with DSW, the actual burden of creating yet another document for a project will become a benefit. In addition, research staff will gain competence in working with data which will help them conduct research more efficiently.

The organization can, on the other hand, monitor, evaluate, and improve local data management. For example, data policies may be updated (and correspondingly the knowledge model in DSW) based on identified issues in existing projects. Then, employees can update the projects and become compliant with the latest data policies by clicking a single button.

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file +Enterprise | Data Stewardship Wizard
DSW
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DSW
Get Started

Enterprise

Thorough data management planning is crucial for research in the enterprise environment. The Data Stewardship Wizard educates its users and helps plan management of data, the precious results of projects.

Enterprise Illustration

Prepare the Content

First, it is necessary to specify what researchers must provide information to plan data management in the organization properly. As each enterprise organization is unique, the way of planning may be more or less different. The Data Stewardship Wizard is ready for that and allows to create knowledge models from scratch and customize existing ones.

Then the replies to a questionnaire specified by the knowledge model may be transformed into different forms suitable for evaluation or other internal/external purposes. By having a custom export template(s), researchers will be able to efficiently provide reports for their projects, just as DMPs for funding agencies.

Learn More

Adjust Look and Feel

Keeping consistent design and branding across information systems is essential in a business environment. DSW can be tailored to use corporate logos, colours, and fonts. Other UI and UX adjustments are also possible using custom stylesheets.

It is possible to also use the same design for exported documents, so all the PDFs from DSW have the colours, fonts, and logo in the header, just as the company's graphic handbook dictates.

Integrate in Workflows and Systems

The Data Stewardship Wizard provides an API that can be used for automation and integration. Hence, other systems in the environment can query and manipulate the content in DSW. For example, whenever a new project is created in the local project management system, a related project is prepared in DSW for specific employees.

Furthermore, DSW can also consume other services such as local SSO, document management systems and databases, controlled vocabularies and repositories with APIs. Thus, the Data Stewardship Wizard can be easily be plugged into the enterprise environment and become part of everyday workflows.

Learn More

Evaluate and Improve

By planning data management with DSW, the actual burden of creating yet another document for a project will become a benefit. In addition, research staff will gain competence in working with data which will help them conduct research more efficiently.

The organization can, on the other hand, monitor, evaluate, and improve local data management. For example, data policies may be updated (and correspondingly the knowledge model in DSW) based on identified issues in existing projects. Then, employees can update the projects and become compliant with the latest data policies by clicking a single button.

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file diff --git a/fair.html b/fair.html index 167a769..a9d1d82 100644 --- a/fair.html +++ b/fair.html @@ -1 +1 @@ -FAIR | Data Stewardship Wizard
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FAIR

The FAIR data recommendations is one of the steps in making data machine-actionable. According to these recommendations, data should be Findable, Accessible, Interoperable, and Reusable. It may not be easy to fully grasp the concept of FAIR, but DSW will make it easier for you, so you can be comfortably up to date with the latest standards.

FAIR Illustration

FAIR Metrics in DSW

You can evaluate answers in each questionnaire to get an overview of how good you are doing in terms of FAIR metrics. Thus you are able to reconsider your decisions already in the planning phase to make your research more FAIR.

FAIR Metrics in DSW

FAIR Guidance

Answers to the questions are marked with labels determining the FAIRness of the answer. This means, when using the DSW, you do not have to know all the FAIR principles and how they work to make your research FAIR. You will know the best approach from the labels and can therefore choose a better way for your research.

FAIR Guidance
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FAIR

The FAIR data recommendations is one of the steps in making data machine-actionable. According to these recommendations, data should be Findable, Accessible, Interoperable, and Reusable. It may not be easy to fully grasp the concept of FAIR, but DSW will make it easier for you, so you can be comfortably up to date with the latest standards.

FAIR Illustration

FAIR Metrics in DSW

You can evaluate answers in each questionnaire to get an overview of how good you are doing in terms of FAIR metrics. Thus you are able to reconsider your decisions already in the planning phase to make your research more FAIR.

FAIR Metrics in DSW

FAIR Guidance

Answers to the questions are marked with labels determining the FAIRness of the answer. This means, when using the DSW, you do not have to know all the FAIR principles and how they work to make your research FAIR. You will know the best approach from the labels and can therefore choose a better way for your research.

FAIR Guidance
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
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Funder

The Data Stewardship Wizard can easily adapt to the needs of funders. DSW will guide grant applicants and gather answers to essential questions for funders in a form that makes evaluation effective.

Funder Illustration

Adopt a Knowledge Model

All questions that are necessary to ask in grant applications can be specified in a Knowledge Model. It allows structure questions into chapters and provides various forms of guidance: references, options, suggestions from integrations, metrics, and more.

A funder may use an existing Knowledge Model and customize it if necessary or build one's own from scratch. Such a Knowledge Model is easy to manage and evolve directly in DSW.

Learn More

Create an Export Template

The document that the applicant gets from DSW can be in any textual format, and it does not have to follow the structure of the Knowledge Model. Moreover, templates can allow export in multiple formats, e.g., JSON for machine-readability, PDF for submission, or MS Word for further edits outside DSW.

For example, a template can transform a grant application into RDF or JSON for automated evaluation in the same way as it can define an excellent looking PDF document.

Learn More

Integrate and Automate

Once the applicant finalizes the document, it can be sent to the funder. Manually reading and evaluating such applications is ineffective. Aside from the evaluation of metrics, DSW allows integration in terms of document submission.

Applicants can directly submit a document to the funder's evaluation service or dedicated storage.

An integration solution study using the Data Stewardship Wizard can be found here: FAIR Made Easy for Funders.

Learn More

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Funder

The Data Stewardship Wizard can easily adapt to the needs of funders. DSW will guide grant applicants and gather answers to essential questions for funders in a form that makes evaluation effective.

Funder Illustration

Adopt a Knowledge Model

All questions that are necessary to ask in grant applications can be specified in a Knowledge Model. It allows structure questions into chapters and provides various forms of guidance: references, options, suggestions from integrations, metrics, and more.

A funder may use an existing Knowledge Model and customize it if necessary or build one's own from scratch. Such a Knowledge Model is easy to manage and evolve directly in DSW.

Learn More

Create an Export Template

The document that the applicant gets from DSW can be in any textual format, and it does not have to follow the structure of the Knowledge Model. Moreover, templates can allow export in multiple formats, e.g., JSON for machine-readability, PDF for submission, or MS Word for further edits outside DSW.

For example, a template can transform a grant application into RDF or JSON for automated evaluation in the same way as it can define an excellent looking PDF document.

Learn More

Integrate and Automate

Once the applicant finalizes the document, it can be sent to the funder. Manually reading and evaluating such applications is ineffective. Aside from the evaluation of metrics, DSW allows integration in terms of document submission.

Applicants can directly submit a document to the funder's evaluation service or dedicated storage.

An integration solution study using the Data Stewardship Wizard can be found here: FAIR Made Easy for Funders.

Learn More

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
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Get Started

Discover different ways to begin using the Data Stewardship Wizard. Various options to start will help you plan and manage your data effectively.

Data Steward Illustration

Self-Hosted

Data Stewardship Wizard is an open-source tool distributed as a set of Docker images that everyone can deploy and use. We provide an extensive guide on deploying, configuring, and maintaining a DSW instance on your own.

Explore guide

Providers

If you don't want to maintain DSW yourself, there are providers managing DSW or solutions based on DSW that you can explore.

DSW Cloud for ELIXIRDSW Cloud for ELIXIRFAIR WizardFAIR WizardFAIR SolutionsFAIR Solutions
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Get Started

Discover different ways to begin using the Data Stewardship Wizard. Various options to start will help you plan and manage your data effectively.

Data Steward Illustration

Self-Hosted

Data Stewardship Wizard is an open-source tool distributed as a set of Docker images that everyone can deploy and use. We provide an extensive guide on deploying, configuring, and maintaining a DSW instance on your own.

Explore guide

Providers

If you don't want to maintain DSW yourself, there are providers managing DSW or solutions based on DSW that you can explore.

DSW Cloud for ELIXIRDSW Cloud for ELIXIRFAIR WizardFAIR WizardFAIR SolutionsFAIR Solutions
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
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Help Center

Explore our Help Center for various support options and find answers to your questions.

Help Center Illustration

Discord Community

Our Discord community is a thriving hub where you can find assistance, connect with others, and get your questions answered. Join us now to experience a welcoming environment filled with helpful members eager to lend a hand.

Join our Discord
Discord Community

GitHub Issues

In our GitHub Issues, you can report software bugs or ask questions, actively participating in our ongoing effort to enhance the user experience.

Report an issue
GitHub Issues

DSW Ideas

Explore DSW Ideas, where you can browse, suggest, discuss, and help prioritize feature requests. Join the conversation, and together, we'll shape the future of our product based on your valuable input.

Suggest an idea
DSW Ideas

Email

If you can't find what you need, feel free to drop us an email – we're here to help!

Send us an email
Email
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Help Center

Explore our Help Center for various support options and find answers to your questions.

Help Center Illustration

Discord Community

Our Discord community is a thriving hub where you can find assistance, connect with others, and get your questions answered. Join us now to experience a welcoming environment filled with helpful members eager to lend a hand.

Join our Discord
Discord Community

GitHub Issues

In our GitHub Issues, you can report software bugs or ask questions, actively participating in our ongoing effort to enhance the user experience.

Report an issue
GitHub Issues

DSW Ideas

Explore DSW Ideas, where you can browse, suggest, discuss, and help prioritize feature requests. Join the conversation, and together, we'll shape the future of our product based on your valuable input.

Suggest an idea
DSW Ideas

Email

If you can't find what you need, feel free to drop us an email – we're here to help!

Send us an email
Email
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Data Stewardship Wizard

Leading open-source platform for collaborative and living data management plans trusted worldwide — from data management pioneers to international research institutes.

Video Thumbnail

Recommended by

Horizon Europe
Programme GuideUB-BOTT
(Universities of Norway)Technology Agency of
the Czech RepublicProgramme Johannes
Amos Comenius
Data Stewardship Wizard Application

Data Stewardship

Data stewardship focuses on tactical coordination and implementation responsible for establishing data-quality metrics and other requirements regarding good data management. The ultimate goal is to provide high-quality data that is easily accessible in a consistent manner.

Learn more
Data Stewardship

Decision Support

Building a data management plan and providing high-quality research data requires many considerations that can be overwhelming and hard to start with. In DSW, you do not have to write a lot of text. Instead, you answer understandable questions in smart questionnaires, get links to external resources, FAIR metrics indications and more. These questions can have some follow-ups based on your answers or can be connected to external resources.

Explore
Decision Support

Collaboration

Nowadays, working in a team is crucial. DSW provides many options on how to share your project with other people. You can work together online, comment questions, and immediately see the changes made by your coworkers. You can quickly see who answered which questions, and all the changes are saved in the version history. You can then label specific versions or come back to any point in history

Collaboration

DSW in Action

Enabling Seamless Data Management Planning within PaNOSC

DSW's integration within the PaNOSC project has streamlined Data Management Planning (DMP) across various Research Infrastructures (RIs), exemplified by ESFR's creation of over 1150 DMPs with 60% auto-population. As more RIs consider making DMPs mandatory, the future holds the promise of machine-readable DMPs for enhanced data exploitation and knowledge graph development.

Read the full story

The Chalmers DS Wizard Story

Chalmers University of Technology is one of the leading science and technology universities in northern Europe, with over 2,000 active researchers, coordinating around 400 new, often highly data intensive research projects yearly.

Read the full story

Story of the DSW Teaching at the Clermont Auvergne University

The University of Clermont Auvergne (UCA) offers a Master's degree in Bioinformatics. One of the teaching units deals with how to handle and share public data considering best practices and FAIR principles for reproducible sciences. DSW has a friendly web interface with various DMP flavors, which makes it rapidly usable by anyone without specific background.

Read the full story

Integrating DSW at IFB

The Institut Français de Bioinformatique (IFB – ELIXIR-FR) installed a DSW instance in the first half of 2021. We are in the process of creating a DMP template targeted to the French bioimagery community and we needed a user-friendly tool to help us build the structure of the DMP, experiment with it, and gather inputs and comments from the various actors.

Read the full story

BioData.pt Experience

BioData.pt is the Portuguese distributed e-infrastructure for biological data and the Portuguese ELIXIR node. Its mission is to support the national scientific system through best practices in data management and state of the art data analysis.

Read the full story

The ELIXIR Norway DSW Story

Norwegian funders require that research groups submit data management plans (DMPs) upon signing the contract for their research projects. Generating a DMP has been regarded by many researchers as a mere administrative burden, rather than a tool to revise their habits and support their projects.

Read the full story

The SciLifeLab DSW Story

Our story started in 2018 with the development of a data management plan (DMP) template targeted at projects generating NGS data at SciLifeLab. We wanted to provide this template to a wider audience and hence needed an online resource. Through the ELIXIR network we knew about the Data Stewardship Wizard, and decided to try it out.

Read the full story

AURORA logoAURORABioData.pt logoBioData.ptCalouste Gulbenkian Foundation logoCalouste Gulbenkian FoundationCentre for Digital Life Norway logoCentre for Digital Life NorwayCERIC-ERIC logoCERIC-ERICChalmers University of Technology logoChalmers University of TechnologyCzech Technical University in Prague logoCzech Technical University in PragueCzech University of Life Sciences Prague logoCzech University of Life Sciences PragueEJP RD logoEJP RDELI-ERIC logoELI-ERICELIXIR Belgium logoELIXIR BelgiumELIXIR Luxembourg logoELIXIR LuxembourgELIXIR Norway logoELIXIR NorwayELIXIR Slovenia logoELIXIR SloveniaENVRI-FAR logoENVRI-FARESRF logoESRFESS logoESSGO FAIR initiative logoGO FAIR initiativeINESC-ID logoINESC-IDInstitut Français de Bioinformatique logoInstitut Français de BioinformatiqueMésocentre University of Clermont Auvergne logoMésocentre University of Clermont AuvergneNational Library of Technology logoNational Library of TechnologyNorwegian University of Life Sciences logoNorwegian University of Life SciencesNorwegian University of Science and Technology logoNorwegian University of Science and TechnologyOpen Science Centre of University of Jyväskylä logoOpen Science Centre of University of JyväskyläPalacký University logoPalacký UniversityPaNOSC Project logoPaNOSC ProjectResearch Data Alliance logoResearch Data AllianceRNAct logoRNActSciLifeLab Data Centre logoSciLifeLab Data CentreSwiss Institute of Bioinformatics logoSwiss Institute of BioinformaticsUniversidade de Lisboa logoUniversidade de LisboaUniversity of Bergen logoUniversity of BergenUniversity of Chemistry and Technology, Prague logoUniversity of Chemistry and Technology, PragueUniversity of Ljubljana logoUniversity of LjubljanaUniversity of Oslo logoUniversity of OsloUniversity of Tromsø logoUniversity of Tromsø

How to Support Us

  • Send us a success story

    Do you use DSW in your research or is it somehow included in your workflow? We would be happy to hear and publish your success story to inspire others!

    Contact us

  • Cite our paper

    If you write a paper where you would like to refer to the Data Stewardship Wizard, we would really appreciate if you cited our DSW paper. Here we provide more details about how to cite us.

    How to cite us

  • Translate to your language

    You can easily contribute just by providing your language skills and help us translate DSW to various languages as well as maintain such translations.

    Translate DSW

  • Sponsor us

    We highly appreciate any form of feedback and support from the community. You or your organisation can support DSW development easily using GitHub Sponsors.

    Sponsor DSW @ GitHub

Acknowledgements

Releases from 4.3 up to 4.8 (see the details) were supported by National Repository Platform project (MŠMT / OP JAK Grant).

OP JAK (EU) and MSMT logo

Releases from 2.3 up to 4.8 (see the details) were supported by Codevence Solutions.

Codevence Solutions logo

Releases from 3.19 up to 4.3 (see the details) were supported by ELIXIR CZ research infrastructure (MŠMT Grant No.: LM2023055).

ELIXIR CZ and MSMT logo

Releases from 2.4 up to 3.24 (see the details) were supported by ELIXIR-CONVERGE project (10.3030/871075).

ELIXIR-CONVERGE logo

Releases from 2.0 up to 3.18 (see the details) were supported by ELIXIR CZ research infrastructure (MŠMT Grant No.: LM2018131).

ELIXIR CZ and MSMT logo

Releases 3.5, 3.6, and 3.7 (see the details) were supported by the ENVRI-FAIR to develop the FIP wizard to generate FAIR Implementation Profiles.

ENVRI-FAIR logo

Releases 2.10, 2.11 and 2.12 (see the details) were supported by the Centre for Digital Life Norway with funding from the Research Council of Norway under grant agreement 248810.

Centre for Digital Life Norway and Research Council of Norway logo

Releases from 1.0 up to 1.10 were developed as part of the ELIXIR Implementation Study Towards Data Stewardship in ELIXIR: Training and Portal.

logo

Releases before version 1.0 were created as part of the diploma theses of Vojtěch Knaisl and Jan Slifka supervised by Robert Pergl submitted at the Faculty of Information Technology, Czech Technical University in Prague.

Faculty of Information Technology, Czech Technical University in Prague logo
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file +Data Stewardship Wizard
DSW
Get Started
DSW
Get Started

Data Stewardship Wizard

Leading open-source platform for collaborative and living data management plans trusted worldwide — from data management pioneers to international research institutes.

Video Thumbnail

Recommended by

Horizon Europe
Programme GuideUB-BOTT
(Universities of Norway)Technology Agency of
the Czech RepublicProgramme Johannes
Amos Comenius
Data Stewardship Wizard Application

Data Stewardship

Data stewardship focuses on tactical coordination and implementation responsible for establishing data-quality metrics and other requirements regarding good data management. The ultimate goal is to provide high-quality data that is easily accessible in a consistent manner.

Learn more
Data Stewardship

Decision Support

Building a data management plan and providing high-quality research data requires many considerations that can be overwhelming and hard to start with. In DSW, you do not have to write a lot of text. Instead, you answer understandable questions in smart questionnaires, get links to external resources, FAIR metrics indications and more. These questions can have some follow-ups based on your answers or can be connected to external resources.

Explore
Decision Support

Collaboration

Nowadays, working in a team is crucial. DSW provides many options on how to share your project with other people. You can work together online, comment questions, and immediately see the changes made by your coworkers. You can quickly see who answered which questions, and all the changes are saved in the version history. You can then label specific versions or come back to any point in history

Collaboration

DSW in Action

Enabling Seamless Data Management Planning within PaNOSC

DSW's integration within the PaNOSC project has streamlined Data Management Planning (DMP) across various Research Infrastructures (RIs), exemplified by ESFR's creation of over 1150 DMPs with 60% auto-population. As more RIs consider making DMPs mandatory, the future holds the promise of machine-readable DMPs for enhanced data exploitation and knowledge graph development.

Read the full story

The Chalmers DS Wizard Story

Chalmers University of Technology is one of the leading science and technology universities in northern Europe, with over 2,000 active researchers, coordinating around 400 new, often highly data intensive research projects yearly.

Read the full story

Story of the DSW Teaching at the Clermont Auvergne University

The University of Clermont Auvergne (UCA) offers a Master's degree in Bioinformatics. One of the teaching units deals with how to handle and share public data considering best practices and FAIR principles for reproducible sciences. DSW has a friendly web interface with various DMP flavors, which makes it rapidly usable by anyone without specific background.

Read the full story

Integrating DSW at IFB

The Institut Français de Bioinformatique (IFB – ELIXIR-FR) installed a DSW instance in the first half of 2021. We are in the process of creating a DMP template targeted to the French bioimagery community and we needed a user-friendly tool to help us build the structure of the DMP, experiment with it, and gather inputs and comments from the various actors.

Read the full story

BioData.pt Experience

BioData.pt is the Portuguese distributed e-infrastructure for biological data and the Portuguese ELIXIR node. Its mission is to support the national scientific system through best practices in data management and state of the art data analysis.

Read the full story

The ELIXIR Norway DSW Story

Norwegian funders require that research groups submit data management plans (DMPs) upon signing the contract for their research projects. Generating a DMP has been regarded by many researchers as a mere administrative burden, rather than a tool to revise their habits and support their projects.

Read the full story

The SciLifeLab DSW Story

Our story started in 2018 with the development of a data management plan (DMP) template targeted at projects generating NGS data at SciLifeLab. We wanted to provide this template to a wider audience and hence needed an online resource. Through the ELIXIR network we knew about the Data Stewardship Wizard, and decided to try it out.

Read the full story

AURORA logoAURORABioData.pt logoBioData.ptCalouste Gulbenkian Foundation logoCalouste Gulbenkian FoundationCentre for Digital Life Norway logoCentre for Digital Life NorwayCERIC-ERIC logoCERIC-ERICChalmers University of Technology logoChalmers University of TechnologyCzech Technical University in Prague logoCzech Technical University in PragueCzech University of Life Sciences Prague logoCzech University of Life Sciences PragueEJP RD logoEJP RDELI-ERIC logoELI-ERICELIXIR Belgium logoELIXIR BelgiumELIXIR Luxembourg logoELIXIR LuxembourgELIXIR Norway logoELIXIR NorwayELIXIR Slovenia logoELIXIR SloveniaENVRI-FAR logoENVRI-FARESRF logoESRFESS logoESSGO FAIR initiative logoGO FAIR initiativeINESC-ID logoINESC-IDInstitut Français de Bioinformatique logoInstitut Français de BioinformatiqueMésocentre University of Clermont Auvergne logoMésocentre University of Clermont AuvergneNational Library of Technology logoNational Library of TechnologyNorwegian University of Life Sciences logoNorwegian University of Life SciencesNorwegian University of Science and Technology logoNorwegian University of Science and TechnologyOpen Science Centre of University of Jyväskylä logoOpen Science Centre of University of JyväskyläPalacký University logoPalacký UniversityPaNOSC Project logoPaNOSC ProjectResearch Data Alliance logoResearch Data AllianceRNAct logoRNActSciLifeLab Data Centre logoSciLifeLab Data CentreSwiss Institute of Bioinformatics logoSwiss Institute of BioinformaticsUniversidade de Lisboa logoUniversidade de LisboaUniversity of Bergen logoUniversity of BergenUniversity of Chemistry and Technology, Prague logoUniversity of Chemistry and Technology, PragueUniversity of Ljubljana logoUniversity of LjubljanaUniversity of Oslo logoUniversity of OsloUniversity of Tromsø logoUniversity of Tromsø

How to Support Us

  • Send us a success story

    Do you use DSW in your research or is it somehow included in your workflow? We would be happy to hear and publish your success story to inspire others!

    Contact us

  • Cite our paper

    If you write a paper where you would like to refer to the Data Stewardship Wizard, we would really appreciate if you cited our DSW paper. Here we provide more details about how to cite us.

    How to cite us

  • Translate to your language

    You can easily contribute just by providing your language skills and help us translate DSW to various languages as well as maintain such translations.

    Translate DSW

  • Sponsor us

    We highly appreciate any form of feedback and support from the community. You or your organisation can support DSW development easily using GitHub Sponsors.

    Sponsor DSW @ GitHub

Acknowledgements

Releases from 4.3 up to 4.10 (see the details) were supported by National Repository Platform project (MŠMT / OP JAK Grant).

OP JAK (EU) and MSMT logo

Releases from 2.3 up to 4.10 (see the details) were supported by Codevence Solutions.

Codevence Solutions logo

Releases from 3.19 up to 4.3 (see the details) were supported by ELIXIR CZ research infrastructure (MŠMT Grant No.: LM2023055).

ELIXIR CZ and MSMT logo

Releases from 2.4 up to 3.24 (see the details) were supported by ELIXIR-CONVERGE project (10.3030/871075).

ELIXIR-CONVERGE logo

Releases from 2.0 up to 3.18 (see the details) were supported by ELIXIR CZ research infrastructure (MŠMT Grant No.: LM2018131).

ELIXIR CZ and MSMT logo

Releases 3.5, 3.6, and 3.7 (see the details) were supported by the ENVRI-FAIR to develop the FIP wizard to generate FAIR Implementation Profiles.

ENVRI-FAIR logo

Releases 2.10, 2.11 and 2.12 (see the details) were supported by the Centre for Digital Life Norway with funding from the Research Council of Norway under grant agreement 248810.

Centre for Digital Life Norway and Research Council of Norway logo

Releases from 1.0 up to 1.10 were developed as part of the ELIXIR Implementation Study Towards Data Stewardship in ELIXIR: Training and Portal.

logo

Releases before version 1.0 were created as part of the diploma theses of Vojtěch Knaisl and Jan Slifka supervised by Robert Pergl submitted at the Faculty of Information Technology, Czech Technical University in Prague.

Faculty of Information Technology, Czech Technical University in Prague logo
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
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DSW
Get Started
DSW
Get Started

Integrating DSW at IFB

The Institut Français de Bioinformatique (IFB – ELIXIR-FR) installed a DSW instance dsw.france-bioinformatique.fr in the first half of 2021. We are in the process of creating a DMP template targeted to the French bioimagery community and we needed a user-friendly tool to help us build the structure of the DMP, experiment with it, and gather inputs and comments from the various actors. We hope to finalise our first version of the DMP model by the end of this year 2021.

DSW has an almost inexistant barrier to entry and is thus an ideal tool to map ideas, to collaborate, and finally to raise awareness about data management as a practice. As an example, an informal group has emerged in the IFB around the question of creating DMPs for infrastructures (as opposed to for projects).

In the future we plan to integrate DSW with DMP OPIDoR (dmp.opidor.fr), the French extension to DMP Roadmap specifically designed for the French research community. DMP OPIDoR plans its first machine-actionable release also towards the end of 2021. Tool integration is a natural evolution and would follow up on work already started by the RDA DMP Common Standard

Paulette Lieby, Institut Français de Bioinformatique (IFB – ELIXIR-FR)

Institut Français de Bioinformatique logo
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
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DSW
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DSW
Get Started

Integrating DSW at IFB

The Institut Français de Bioinformatique (IFB – ELIXIR-FR) installed a DSW instance dsw.france-bioinformatique.fr in the first half of 2021. We are in the process of creating a DMP template targeted to the French bioimagery community and we needed a user-friendly tool to help us build the structure of the DMP, experiment with it, and gather inputs and comments from the various actors. We hope to finalise our first version of the DMP model by the end of this year 2021.

DSW has an almost inexistant barrier to entry and is thus an ideal tool to map ideas, to collaborate, and finally to raise awareness about data management as a practice. As an example, an informal group has emerged in the IFB around the question of creating DMPs for infrastructures (as opposed to for projects).

In the future we plan to integrate DSW with DMP OPIDoR (dmp.opidor.fr), the French extension to DMP Roadmap specifically designed for the French research community. DMP OPIDoR plans its first machine-actionable release also towards the end of 2021. Tool integration is a natural evolution and would follow up on work already started by the RDA DMP Common Standard

Paulette Lieby, Institut Français de Bioinformatique (IFB – ELIXIR-FR)

Institut Français de Bioinformatique logo
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
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Integrations

The Data Stewardship Wizard is an application that is ready for integration with other services. Such services can be both public and private. By integrating DSW with other services in the environment, data management planning becomes even more convenient.

Integrations Illustration

Integration Questions

Questionnaires can be connected to external sources. Apart from getting to the answer being fast and easy, it also becomes automatically FAIR. For example, DSW is currently connected to FAIRsharing so you can enjoy their high-quality curated content around databases, standards and policies.

Integration Questions

Submission Services

Once a user creates a document using a specific template, it can be downloaded from DSW. But there is another option. DSW can be configured to allow document submission for a specific template and format. For example, a user creates Horizon 2020 DMP in PDF format which can then be submitted to a different service for review. Similarly, machine-actionable DMP in RDF format can be submitted through a specialized service to a triple store.

The intermediary services handling submission are usually needed to be tailored based on specific requirements of an organization.

Submission Services

Single Sign-On

Creating an account in DSW through the registration form is just one of the options. OpenID Connect standard for connecting identity provider services is supported directly in DSW and configurable by an administrator in the user interface. The advantages are evident. Users do not have to create another account and remember a password. Instead, they can easily use existing accounts from institutions or other services, for example, Google.

Single Sign-On

Documented API

The Data Stewardship Wizard provides REST API which is mainly consumed by our official client web application. However, it can be used in other services and scripts for integration purposes. The API can be used to query and manipulate data in DSW. For example, one may develop a script to collect FAIR metrics evaluation of all projects. There is Swagger API documentation embedded in each DSW instance.

Documented API
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Integrations

The Data Stewardship Wizard is an application that is ready for integration with other services. Such services can be both public and private. By integrating DSW with other services in the environment, data management planning becomes even more convenient.

Integrations Illustration

Integration Questions

Questionnaires can be connected to external sources. Apart from getting to the answer being fast and easy, it also becomes automatically FAIR. For example, DSW is currently connected to FAIRsharing so you can enjoy their high-quality curated content around databases, standards and policies.

Integration Questions

Submission Services

Once a user creates a document using a specific template, it can be downloaded from DSW. But there is another option. DSW can be configured to allow document submission for a specific template and format. For example, a user creates Horizon 2020 DMP in PDF format which can then be submitted to a different service for review. Similarly, machine-actionable DMP in RDF format can be submitted through a specialized service to a triple store.

The intermediary services handling submission are usually needed to be tailored based on specific requirements of an organization.

Submission Services

Single Sign-On

Creating an account in DSW through the registration form is just one of the options. OpenID Connect standard for connecting identity provider services is supported directly in DSW and configurable by an administrator in the user interface. The advantages are evident. Users do not have to create another account and remember a password. Instead, they can easily use existing accounts from institutions or other services, for example, Google.

Single Sign-On

Documented API

The Data Stewardship Wizard provides REST API which is mainly consumed by our official client web application. However, it can be used in other services and scripts for integration purposes. The API can be used to query and manipulate data in DSW. For example, one may develop a script to collect FAIR metrics evaluation of all projects. There is Swagger API documentation embedded in each DSW instance.

Documented API
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\ No newline at end of file diff --git a/knowledge-models.html b/knowledge-models.html index 3e9dc9e..e054aa2 100644 --- a/knowledge-models.html +++ b/knowledge-models.html @@ -1 +1 @@ -Knowledge Models | Data Stewardship Wizard
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Knowledge Models

Knowledge Models are basically templates determining the structure of Questionnaires. When creating a new Questionnaire, you are always choosing the Knowledge Model the most suitable for you and your research.

Knowledge Models Illustration

Knowledge Model Structure

A Knowledge Model is divided into chapters, which are composed of questions. The questions include possible answers, references, and FAIR metric labels where relevant. There are also follow-up questions that depend on the previous answer. This way you do not have to answer questions irrelevant to your research.

Knowledge Model Structure

Evolvability

It is a common practice that Knowledge Models have to change sometimes. When a parent Knowledge Model has a new version, its customizations have the option to upgrade so all the Knowledge Models can still be up to date. There is also a very similar process for Questionnaires when their Knowledge Model changes.

Evolvability

Ready to Use Knowledge Models

You can build your own Knowledge Model or you can choose a ready-to-use one. There are a couple of default Knowledge Models that you can choose from. The Common DSW Knowledge Model originates from a mind map made by Rob Hooft, or its customization for Life Sciences.

Ready to Use Knowledge Models

Knowledge Model Editor

The Knowledge Model Editor is a tool for building your own new Knowledge Models or extending the existing ones so that they can cover new areas of expertise or better fit your organization’s needs.

Knowledge Model Editor
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Knowledge Models

Knowledge Models are basically templates determining the structure of Questionnaires. When creating a new Questionnaire, you are always choosing the Knowledge Model the most suitable for you and your research.

Knowledge Models Illustration

Knowledge Model Structure

A Knowledge Model is divided into chapters, which are composed of questions. The questions include possible answers, references, and FAIR metric labels where relevant. There are also follow-up questions that depend on the previous answer. This way you do not have to answer questions irrelevant to your research.

Knowledge Model Structure

Evolvability

It is a common practice that Knowledge Models have to change sometimes. When a parent Knowledge Model has a new version, its customizations have the option to upgrade so all the Knowledge Models can still be up to date. There is also a very similar process for Questionnaires when their Knowledge Model changes.

Evolvability

Ready to Use Knowledge Models

You can build your own Knowledge Model or you can choose a ready-to-use one. There are a couple of default Knowledge Models that you can choose from. The Common DSW Knowledge Model originates from a mind map made by Rob Hooft, or its customization for Life Sciences.

Ready to Use Knowledge Models

Knowledge Model Editor

The Knowledge Model Editor is a tool for building your own new Knowledge Models or extending the existing ones so that they can cover new areas of expertise or better fit your organization’s needs.

Knowledge Model Editor
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\ No newline at end of file diff --git a/machine-actionability.html b/machine-actionability.html index 59ed38b..324935f 100644 --- a/machine-actionability.html +++ b/machine-actionability.html @@ -1 +1 @@ -Machine-Actionability | Data Stewardship Wizard
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Machine-Actionability

Machine-Actionability refers to the information that is consistently structured so that machines can be programmed against such a structure. It is emphasised lately in the domain of data management plans and metadata, as tools need to process and evaluate them effectively.

Machine-Actionability Illustration

Machine-Actionable DMP

Machine-actionable DMP (maDMP) is an emerging standard for adding machine-actionable richness to data management plans to bring added value to all stakeholders. The goal is to enable a frictionless exchange of information across research tools and systems and eventually reduce the administrative burden. DSW is compliant with the maDMP.

Machine-Actionable DMP

Machine-Actionable Export

Not only human-readable documents but also machine-actionable formats like JSON or RDF/XML can be exported from the filled in questionnaires. Furthermore, the Data Stewardship Wizard was developed to use a bare minimum of free text and uses UUID for each question and answer in its machine-actionable DMP (maDMP). Thus it is easy to integrate the data from DSW to other systems.

Machine-Actionable Export
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Machine-Actionability

Machine-Actionability refers to the information that is consistently structured so that machines can be programmed against such a structure. It is emphasised lately in the domain of data management plans and metadata, as tools need to process and evaluate them effectively.

Machine-Actionability Illustration

Machine-Actionable DMP

Machine-actionable DMP (maDMP) is an emerging standard for adding machine-actionable richness to data management plans to bring added value to all stakeholders. The goal is to enable a frictionless exchange of information across research tools and systems and eventually reduce the administrative burden. DSW is compliant with the maDMP.

Machine-Actionable DMP

Machine-Actionable Export

Not only human-readable documents but also machine-actionable formats like JSON or RDF/XML can be exported from the filled in questionnaires. Furthermore, the Data Stewardship Wizard was developed to use a bare minimum of free text and uses UUID for each question and answer in its machine-actionable DMP (maDMP). Thus it is easy to integrate the data from DSW to other systems.

Machine-Actionable Export
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\ No newline at end of file diff --git a/media.html b/media.html index c53fa29..21bd99a 100644 --- a/media.html +++ b/media.html @@ -1 +1 @@ -Media | Data Stewardship Wizard
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Media

Do you want to write about, present or somehow mention the Data Stewardship Wizard? We are happy about it and to make it easier for you, we've prepared a Media Kit with materials (logo variants, screenshots, diagrams, etc.) that you can download and use!

Download Media Kit

When using the logo, please don't change the colours, use one of the variants available in the Media Kit. Give it some space, at least the width of the letter D around the logo (images in the Media Kit have enough padding for that). Also, use the variant with the full text 'DATA STEWARDSHIP WIZARD' only if it's well readable, otherwise use another one.

Media Kit Illustration
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Media

Do you want to write about, present or somehow mention the Data Stewardship Wizard? We are happy about it and to make it easier for you, we've prepared a Media Kit with materials (logo variants, screenshots, diagrams, etc.) that you can download and use!

Download Media Kit

When using the logo, please don't change the colours, use one of the variants available in the Media Kit. Give it some space, at least the width of the letter D around the logo (images in the Media Kit have enough padding for that). Also, use the variant with the full text 'DATA STEWARDSHIP WIZARD' only if it's well readable, otherwise use another one.

Media Kit Illustration
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\ No newline at end of file diff --git a/researcher.html b/researcher.html index 6c392b5..5a31b39 100644 --- a/researcher.html +++ b/researcher.html @@ -1 +1 @@ -Researcher | Data Stewardship Wizard
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Researcher

The main goal of the researchers in the Data Stewardship Wizard is to consider all the challenges and plan how they will work with the data before, during and after the experiment, and of course, get the Data Management Plan (DMP).

Researcher Illustration

Pick a Knowledge Model

Knowledge Model is a tree-like structure of chapters, questions, answers, references and more that captures the knowledge of what should be considered in a DMP and the research experiment in general.

It is not bound to a specific DMP template but a research field or institution. Knowledge Models are provided by DSW itself or by institutional data stewards.

Learn More

Plan, Collaborate

The Knowledge Model is a template for a comprehensive smart questionnaire. Once you pick one, you can start filling in answers related to your research. Even though the questionnaires are usually very complex, you don't have to answer everything at once. Different questions become relevant in different experiment phases, so you only fill in what you need.

Research is teamwork more often than not. In DSW, it is easy to share the project with your colleagues and work on the DMP together online.

Learn More

Get Your DMPs

The significant advantage of the Knowledge Models is that they are not bound to a specific DMP template. Once you have your answers, you can choose what DMP template to use. Do you need a document following the Science Europe recommendations or the machine-actionable DMP? No problem, you simply pick the DMP template and get your answers transformed into the desired form with a single click.

Learn More

Maintain and Evolve

Things change through time, and it's important to keep your project and DMPs updated. You can easily improve and change your answers and generate updated DMPs while keeping all the previous generated documents stored in DSW. You can explore the history of all the changes made to the projects, name important versions or come back to any point in the project's history.

The DMP is not the only thing that evolves. Knowledge Models and DMP templates get updated as well. But don't worry, with DSW, it is easy to update your project to newer versions of the Knowledge Models and keep everything up to date!

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\ No newline at end of file +Researcher | Data Stewardship Wizard
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Researcher

The main goal of the researchers in the Data Stewardship Wizard is to consider all the challenges and plan how they will work with the data before, during and after the experiment, and of course, get the Data Management Plan (DMP).

Researcher Illustration

Pick a Knowledge Model

Knowledge Model is a tree-like structure of chapters, questions, answers, references and more that captures the knowledge of what should be considered in a DMP and the research experiment in general.

It is not bound to a specific DMP template but a research field or institution. Knowledge Models are provided by DSW itself or by institutional data stewards.

Learn More

Plan, Collaborate

The Knowledge Model is a template for a comprehensive smart questionnaire. Once you pick one, you can start filling in answers related to your research. Even though the questionnaires are usually very complex, you don't have to answer everything at once. Different questions become relevant in different experiment phases, so you only fill in what you need.

Research is teamwork more often than not. In DSW, it is easy to share the project with your colleagues and work on the DMP together online.

Learn More

Get Your DMPs

The significant advantage of the Knowledge Models is that they are not bound to a specific DMP template. Once you have your answers, you can choose what DMP template to use. Do you need a document following the Science Europe recommendations or the machine-actionable DMP? No problem, you simply pick the DMP template and get your answers transformed into the desired form with a single click.

Learn More

Maintain and Evolve

Things change through time, and it's important to keep your project and DMPs updated. You can easily improve and change your answers and generate updated DMPs while keeping all the previous generated documents stored in DSW. You can explore the history of all the changes made to the projects, name important versions or come back to any point in the project's history.

The DMP is not the only thing that evolves. Knowledge Models and DMP templates get updated as well. But don't worry, with DSW, it is easy to update your project to newer versions of the Knowledge Models and keep everything up to date!

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
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\ No newline at end of file diff --git a/resources.html b/resources.html index 7406076..15894fa 100644 --- a/resources.html +++ b/resources.html @@ -1 +1 @@ -Resources | Data Stewardship Wizard
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Resources

Learn more about Data Stewardship Wizard from publications, posters, and other online resources.

Resources Illustration

How to Cite Us

Share your resources

Do you have a DSW publication or insights to share? We want to hear from you! Share it with us, and we'll make sure to add your work to our growing list of resources!

Contact us

DSW Team Publications

Technical Resources

Posters

Other Resources

External Publications

Comparative Studies

Case Studies & Use Case Papers

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Resources

Learn more about Data Stewardship Wizard from publications, posters, and other online resources.

Resources Illustration

How to Cite Us

Share your resources

Do you have a DSW publication or insights to share? We want to hear from you! Share it with us, and we'll make sure to add your work to our growing list of resources!

Contact us

DSW Team Publications

Technical Resources

Posters

Other Resources

External Publications

Comparative Studies

Case Studies & Use Case Papers

Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file diff --git a/scilifelab-dsw-story.html b/scilifelab-dsw-story.html index 8ef6cb6..20cc5cb 100644 --- a/scilifelab-dsw-story.html +++ b/scilifelab-dsw-story.html @@ -1 +1 @@ -The SciLifeLab DS Wizard Story | Data Stewardship Wizard
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The SciLifeLab DS Wizard Story

Our story started in 2018 with the development of a data management plan (DMP) template targeted at projects generating NGS data at SciLifeLab. We wanted to provide this template to a wider audience and hence needed an online resource. Through the ELIXIR network we knew about the Data Stewardship Wizard, and decided to try it out. We have two installations of the wizard, one playground for testing and one for serious use, both open for the nation-wide life science community.

The main advantage of this tool is the many possibilities to guide the user through the process of writing a DMP, not only with written advice but also with the hierarchical question structure (less overwhelming), different answer types (enable less free text fields), and possibility of suggested answers and validation using integration to registries of tools, data types, standards, and repositories. Another advantage with this tool is the ease of creating knowledge models (KM) from scratch, and to update them when necessary. We have developed our own KM, based on the initial template and adapted it to adhere to the national guidelines. We also appreciate its provisions for interoperability, making it easier to create DMPs that are in themselves machine readable and FAIR.

During 2019, the awareness in the Swedish research community of the necessity of good data management practices and open science has evolved, and both funders as well as research infrastructures now require, or are in the process of requiring, DMPs on granted projects. We have had two successful workshops, ‘Bring your own DMP’ events, giving hands-on consultation and demonstrating the usefulness of the wizard. The need for a FAIR and flexible tool will keep on increasing and we look forward to a continued journey with DSW and the team behind it.

Yvonne Kallberg, NBIS, SciLifeLab, Stockholm University
Niclas Jareborg, NBIS, SciLifeLab, Stockholm University
Hanna Kultima, SciLifeLab Data Centre, Uppsala University
Johan Rung, SciLifeLab Data Centre, Uppsala University

SciLifeLab logo
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\ No newline at end of file +The SciLifeLab DS Wizard Story | Data Stewardship Wizard
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The SciLifeLab DS Wizard Story

Our story started in 2018 with the development of a data management plan (DMP) template targeted at projects generating NGS data at SciLifeLab. We wanted to provide this template to a wider audience and hence needed an online resource. Through the ELIXIR network we knew about the Data Stewardship Wizard, and decided to try it out. We have two installations of the wizard, one playground for testing and one for serious use, both open for the nation-wide life science community.

The main advantage of this tool is the many possibilities to guide the user through the process of writing a DMP, not only with written advice but also with the hierarchical question structure (less overwhelming), different answer types (enable less free text fields), and possibility of suggested answers and validation using integration to registries of tools, data types, standards, and repositories. Another advantage with this tool is the ease of creating knowledge models (KM) from scratch, and to update them when necessary. We have developed our own KM, based on the initial template and adapted it to adhere to the national guidelines. We also appreciate its provisions for interoperability, making it easier to create DMPs that are in themselves machine readable and FAIR.

During 2019, the awareness in the Swedish research community of the necessity of good data management practices and open science has evolved, and both funders as well as research infrastructures now require, or are in the process of requiring, DMPs on granted projects. We have had two successful workshops, ‘Bring your own DMP’ events, giving hands-on consultation and demonstrating the usefulness of the wizard. The need for a FAIR and flexible tool will keep on increasing and we look forward to a continued journey with DSW and the team behind it.

Yvonne Kallberg, NBIS, SciLifeLab, Stockholm University
Niclas Jareborg, NBIS, SciLifeLab, Stockholm University
Hanna Kultima, SciLifeLab Data Centre, Uppsala University
Johan Rung, SciLifeLab Data Centre, Uppsala University

SciLifeLab logo
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\ No newline at end of file diff --git a/sitemap.xml b/sitemap.xml index 699dbb2..2aa06b6 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -1 +1 @@ -https://ds-wizard.org/4042024-09-12T05:48:36.000Zhttps://ds-wizard.org/about2024-09-12T05:48:36.000Zhttps://ds-wizard.org/beyond-data-management-plans2024-09-12T05:48:36.000Zhttps://ds-wizard.org/biodata-pt-experience2024-09-12T05:48:36.000Zhttps://ds-wizard.org/comparison2024-09-12T05:48:36.000Zhttps://ds-wizard.org/contact2024-09-12T05:48:36.000Zhttps://ds-wizard.org/cookie-policy2024-09-12T05:48:36.000Zhttps://ds-wizard.org/data-management-plans2024-09-12T05:48:36.000Zhttps://ds-wizard.org/data-steward2024-09-12T05:48:36.000Zhttps://ds-wizard.org/data-stewardship2024-09-12T05:48:36.000Zhttps://ds-wizard.org/dmponline-alternative2024-09-12T05:48:36.000Zhttps://ds-wizard.org/document-templates2024-09-12T05:48:36.000Zhttps://ds-wizard.org/dsw-story2024-09-12T05:48:36.000Zhttps://ds-wizard.org/elixir-norway-dsw-story2024-09-12T05:48:36.000Zhttps://ds-wizard.org/enabling-seamless-dmp-within-panocs2024-09-12T05:48:36.000Zhttps://ds-wizard.org/enterprise2024-09-12T05:48:36.000Zhttps://ds-wizard.org/fair2024-09-12T05:48:36.000Zhttps://ds-wizard.org/funder2024-09-12T05:48:36.000Zhttps://ds-wizard.org/get-started2024-09-12T05:48:36.000Zhttps://ds-wizard.org/help-center2024-09-12T05:48:36.000Zhttps://ds-wizard.org/index2024-09-12T05:48:36.000Zhttps://ds-wizard.org/integrating-dsw-at-ifb2024-09-12T05:48:36.000Zhttps://ds-wizard.org/integrations2024-09-12T05:48:36.000Zhttps://ds-wizard.org/knowledge-models2024-09-12T05:48:36.000Zhttps://ds-wizard.org/machine-actionability2024-09-12T05:48:36.000Zhttps://ds-wizard.org/media2024-09-12T05:48:36.000Zhttps://ds-wizard.org/researcher2024-09-12T05:48:36.000Zhttps://ds-wizard.org/resources2024-09-12T05:48:36.000Zhttps://ds-wizard.org/scilifelab-dsw-story2024-09-12T05:48:36.000Zhttps://ds-wizard.org/story-dsw-clermont-auvergne-university2024-09-12T05:48:36.000Zhttps://ds-wizard.org/success-stories2024-09-12T05:48:36.000Zhttps://ds-wizard.org/the-chalmers-ds-wizard-story2024-09-12T05:48:36.000Zhttps://ds-wizard.org/translate-dsw2024-09-12T05:48:36.000Zhttps://ds-wizard.org/university2024-09-12T05:48:36.000Zhttps://ds-wizard.org/video-tutorials2024-09-12T05:48:36.000Z \ No newline at end of file +https://ds-wizard.org/4042024-09-12T06:58:42.000Zhttps://ds-wizard.org/about2024-09-12T06:58:42.000Zhttps://ds-wizard.org/beyond-data-management-plans2024-09-12T06:58:42.000Zhttps://ds-wizard.org/biodata-pt-experience2024-09-12T06:58:42.000Zhttps://ds-wizard.org/comparison2024-09-12T06:58:42.000Zhttps://ds-wizard.org/contact2024-09-12T06:58:42.000Zhttps://ds-wizard.org/cookie-policy2024-09-12T06:58:42.000Zhttps://ds-wizard.org/data-management-plans2024-09-12T06:58:42.000Zhttps://ds-wizard.org/data-steward2024-09-12T06:58:42.000Zhttps://ds-wizard.org/data-stewardship2024-09-12T06:58:42.000Zhttps://ds-wizard.org/dmponline-alternative2024-09-12T06:58:42.000Zhttps://ds-wizard.org/document-templates2024-09-12T06:58:42.000Zhttps://ds-wizard.org/dsw-story2024-09-12T06:58:42.000Zhttps://ds-wizard.org/elixir-norway-dsw-story2024-09-12T06:58:42.000Zhttps://ds-wizard.org/enabling-seamless-dmp-within-panocs2024-09-12T06:58:42.000Zhttps://ds-wizard.org/enterprise2024-09-12T06:58:42.000Zhttps://ds-wizard.org/fair2024-09-12T06:58:42.000Zhttps://ds-wizard.org/funder2024-09-12T06:58:42.000Zhttps://ds-wizard.org/get-started2024-09-12T06:58:42.000Zhttps://ds-wizard.org/help-center2024-09-12T06:58:42.000Zhttps://ds-wizard.org/index2024-09-12T06:58:42.000Zhttps://ds-wizard.org/integrating-dsw-at-ifb2024-09-12T06:58:42.000Zhttps://ds-wizard.org/integrations2024-09-12T06:58:42.000Zhttps://ds-wizard.org/knowledge-models2024-09-12T06:58:42.000Zhttps://ds-wizard.org/machine-actionability2024-09-12T06:58:42.000Zhttps://ds-wizard.org/media2024-09-12T06:58:42.000Zhttps://ds-wizard.org/researcher2024-09-12T06:58:42.000Zhttps://ds-wizard.org/resources2024-09-12T06:58:42.000Zhttps://ds-wizard.org/scilifelab-dsw-story2024-09-12T06:58:42.000Zhttps://ds-wizard.org/story-dsw-clermont-auvergne-university2024-09-12T06:58:42.000Zhttps://ds-wizard.org/success-stories2024-09-12T06:58:42.000Zhttps://ds-wizard.org/the-chalmers-ds-wizard-story2024-09-12T06:58:42.000Zhttps://ds-wizard.org/translate-dsw2024-09-12T06:58:42.000Zhttps://ds-wizard.org/university2024-09-12T06:58:42.000Zhttps://ds-wizard.org/video-tutorials2024-09-12T06:58:42.000Z \ No newline at end of file diff --git a/sitemap.xml.gz b/sitemap.xml.gz index 3424ea7f865eefea3a1312db98a10eb920927950..342f3227e04a0f00a6e8d4f117e5e407dccc13c9 100644 GIT binary patch delta 363 zcmV-x0hIp31j7W7;eU@`?vMLj-L~xyE_VerDSH83H%(j*bgLWmi`G1^y2AWdKVULFk0S*DVX_)Gx8kFj>=(2YzWe< z_4-3uAA-cx%o8d-fwBB9>i3eUsyXuJZ{1?7$_jCayHgHrD$lDq@c*IHyqt&6zW|I^ JKV&`+006o#vCjYi delta 363 zcmV-x0hIp31j7W7;eU?%`{Ui$x^3GZT=rVgHKpl4Iz#X0EY!Qln|Fg6AcL~tSSyPz zt6;z-DN6E%E@Xw*fRT6$zCNnZ)j76tgESES-;1qko2mt`wE?aeXLHcA zL!(Lv)?iACP2++*ky8Pj*HSvNR~Q4wj?_dv0Y$0Svl~#V`G}bEPBWDRu?fQ8@R`k?MlX-A-zCqr2(RV)q! zLcJq$R7Ku`N@UG06Zko5u^&j%Ed3K2=*82$^e!ygV6?mqQ!w)pXXH7U9hJk5*bt;y z>-C4SJ_L!WnI}|w0%Q4I)bAxxRdeLc-@3(El@;O;cc&cMRGwFJ;QvFXc{vZCe*r%P Jd)Gb>0027Yt-AmK diff --git a/story-dsw-clermont-auvergne-university.html b/story-dsw-clermont-auvergne-university.html index 980fed1..8e9906f 100644 --- a/story-dsw-clermont-auvergne-university.html +++ b/story-dsw-clermont-auvergne-university.html @@ -1 +1 @@ -Story of the DSW Teaching at the Clermont Auvergne University | Data Stewardship Wizard
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Story of the DSW Teaching at the Clermont Auvergne University

The University of Clermont Auvergne (UCA) offers a Master's degree in Bioinformatics. One of the teaching units deals with the discovery of an HPC infrastructure and how to handle and share public data considering best practices and FAIR principles for reproducible sciences. DSW has a friendly web interface with various DMP flavors, which makes it rapidly usable by anyone without specific background. Therefore, students discover the benefits of data management, such as having a reflection on data storage and guidelines for data analysis through the lens of the data life cycle.

After intending a DSW practice done by ELIXIR-Luxembourg in 2020, we got the opportunity to have an annual temporary DSW server instance for teaching with effective administration support. Students handle their HPC project and use DSW as a tool to bring out questioning on data (usage, analysis, storage …) as well as metadata and standards.

Through this training approach, we hope to open students' minds to help them integrate best practices for reproducible sciences and be up-to-date when integrating real science projects during their internships.

Nadia Goué, AuBi platform, Mésocentre Clermont-Auvergne, UCA, France

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Story of the DSW Teaching at the Clermont Auvergne University

The University of Clermont Auvergne (UCA) offers a Master's degree in Bioinformatics. One of the teaching units deals with the discovery of an HPC infrastructure and how to handle and share public data considering best practices and FAIR principles for reproducible sciences. DSW has a friendly web interface with various DMP flavors, which makes it rapidly usable by anyone without specific background. Therefore, students discover the benefits of data management, such as having a reflection on data storage and guidelines for data analysis through the lens of the data life cycle.

After intending a DSW practice done by ELIXIR-Luxembourg in 2020, we got the opportunity to have an annual temporary DSW server instance for teaching with effective administration support. Students handle their HPC project and use DSW as a tool to bring out questioning on data (usage, analysis, storage …) as well as metadata and standards.

Through this training approach, we hope to open students' minds to help them integrate best practices for reproducible sciences and be up-to-date when integrating real science projects during their internships.

Nadia Goué, AuBi platform, Mésocentre Clermont-Auvergne, UCA, France

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Success Stories

Read the stories of organizations and institutions who shared their experience with using the Data Stewardship Wizard.

Success Stories Illustration

Enabling Seamless Data Management Planning within PaNOSC

DSW's integration within the PaNOSC project has streamlined Data Management Planning (DMP) across various Research Infrastructures (RIs), exemplified by ESFR's creation of over 1150 DMPs with 60% auto-population. As more RIs consider making DMPs mandatory, the future holds the promise of machine-readable DMPs for enhanced data exploitation and knowledge graph development.

Read the full story
Enabling Seamless Data Management Planning within PaNOSC

The Chalmers DS Wizard Story

Chalmers University of Technology is one of the leading science and technology universities in northern Europe, with over 2,000 active researchers, coordinating around 400 new, often highly data intensive research projects yearly.

Read the full story
The Chalmers DS Wizard Story

Story of the DSW Teaching at the Clermont Auvergne University

The University of Clermont Auvergne (UCA) offers a Master's degree in Bioinformatics. One of the teaching units deals with how to handle and share public data considering best practices and FAIR principles for reproducible sciences. DSW has a friendly web interface with various DMP flavors, which makes it rapidly usable by anyone without specific background.

Read the full story
Story of the DSW Teaching at the Clermont Auvergne University

Integrating DSW at IFB

The Institut Français de Bioinformatique (IFB – ELIXIR-FR) installed a DSW instance in the first half of 2021. We are in the process of creating a DMP template targeted to the French bioimagery community and we needed a user-friendly tool to help us build the structure of the DMP, experiment with it, and gather inputs and comments from the various actors.

Read the full story
Integrating DSW at IFB

BioData.pt Experience

BioData.pt is the Portuguese distributed e-infrastructure for biological data and the Portuguese ELIXIR node. Its mission is to support the national scientific system through best practices in data management and state of the art data analysis.

Read the full story
BioData.pt Experience

The ELIXIR Norway DSW Story

Norwegian funders require that research groups submit data management plans (DMPs) upon signing the contract for their research projects. Generating a DMP has been regarded by many researchers as a mere administrative burden, rather than a tool to revise their habits and support their projects.

Read the full story
The ELIXIR Norway DSW Story

The SciLifeLab DSW Story

Our story started in 2018 with the development of a data management plan (DMP) template targeted at projects generating NGS data at SciLifeLab. We wanted to provide this template to a wider audience and hence needed an online resource. Through the ELIXIR network we knew about the Data Stewardship Wizard, and decided to try it out.

Read the full story
The SciLifeLab DSW Story
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DSW
Get Started
DSW
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Success Stories

Read the stories of organizations and institutions who shared their experience with using the Data Stewardship Wizard.

Success Stories Illustration

Enabling Seamless Data Management Planning within PaNOSC

DSW's integration within the PaNOSC project has streamlined Data Management Planning (DMP) across various Research Infrastructures (RIs), exemplified by ESFR's creation of over 1150 DMPs with 60% auto-population. As more RIs consider making DMPs mandatory, the future holds the promise of machine-readable DMPs for enhanced data exploitation and knowledge graph development.

Read the full story
Enabling Seamless Data Management Planning within PaNOSC

The Chalmers DS Wizard Story

Chalmers University of Technology is one of the leading science and technology universities in northern Europe, with over 2,000 active researchers, coordinating around 400 new, often highly data intensive research projects yearly.

Read the full story
The Chalmers DS Wizard Story

Story of the DSW Teaching at the Clermont Auvergne University

The University of Clermont Auvergne (UCA) offers a Master's degree in Bioinformatics. One of the teaching units deals with how to handle and share public data considering best practices and FAIR principles for reproducible sciences. DSW has a friendly web interface with various DMP flavors, which makes it rapidly usable by anyone without specific background.

Read the full story
Story of the DSW Teaching at the Clermont Auvergne University

Integrating DSW at IFB

The Institut Français de Bioinformatique (IFB – ELIXIR-FR) installed a DSW instance in the first half of 2021. We are in the process of creating a DMP template targeted to the French bioimagery community and we needed a user-friendly tool to help us build the structure of the DMP, experiment with it, and gather inputs and comments from the various actors.

Read the full story
Integrating DSW at IFB

BioData.pt Experience

BioData.pt is the Portuguese distributed e-infrastructure for biological data and the Portuguese ELIXIR node. Its mission is to support the national scientific system through best practices in data management and state of the art data analysis.

Read the full story
BioData.pt Experience

The ELIXIR Norway DSW Story

Norwegian funders require that research groups submit data management plans (DMPs) upon signing the contract for their research projects. Generating a DMP has been regarded by many researchers as a mere administrative burden, rather than a tool to revise their habits and support their projects.

Read the full story
The ELIXIR Norway DSW Story

The SciLifeLab DSW Story

Our story started in 2018 with the development of a data management plan (DMP) template targeted at projects generating NGS data at SciLifeLab. We wanted to provide this template to a wider audience and hence needed an online resource. Through the ELIXIR network we knew about the Data Stewardship Wizard, and decided to try it out.

Read the full story
The SciLifeLab DSW Story
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The Chalmers DS Wizard Story

Chalmers University of Technology is one of the leading science and technology universities in northern Europe, with over 2,000 active researchers, coordinating around 400 new, often highly data intensive research projects yearly. Data management planning, at an early stage of a project, is regarded as very important and the university has accordingly adapted steering guidelines stating that all research activities should have a DMP.

Our story started in 2020, when a local instance of DS Wizard was chosen and implemented as the recommended tool for data management planning at the university. The main reason for this choice was that we found it to be not only the most modern and flexible of the available tools, built on a solid platform and including an appealing and versatile user interface, but also - with its data model and focus on machine actionable DMPs - very well-tailored for integration in our existing (and future) workflows.

We have a history of agile development, automation and creating integrations in order to provide good services and value for our researchers, including a locally developed CRIS, and DS Wizard fitted perfectly into this with its API, standardized data model, configurable templates and SSO support. There is now an automated workflow in place, to help researchers getting started with data management planning, while controlling the quality of the metadata and connecting to other services and stakeholders, such as the data protection office. This has not only helped our researchers, by lowering the barriers, but also created a good foundation for building better services in the future, with integrations, high quality metadata and better user experiences for everyone involved.

Urban Andersson, Chalmers Data Office (CDO), Chalmers University of Technology, Gothenburg

Chalmers University of Technology
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\ No newline at end of file +The Chalmers DS Wizard Story | Data Stewardship Wizard
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The Chalmers DS Wizard Story

Chalmers University of Technology is one of the leading science and technology universities in northern Europe, with over 2,000 active researchers, coordinating around 400 new, often highly data intensive research projects yearly. Data management planning, at an early stage of a project, is regarded as very important and the university has accordingly adapted steering guidelines stating that all research activities should have a DMP.

Our story started in 2020, when a local instance of DS Wizard was chosen and implemented as the recommended tool for data management planning at the university. The main reason for this choice was that we found it to be not only the most modern and flexible of the available tools, built on a solid platform and including an appealing and versatile user interface, but also - with its data model and focus on machine actionable DMPs - very well-tailored for integration in our existing (and future) workflows.

We have a history of agile development, automation and creating integrations in order to provide good services and value for our researchers, including a locally developed CRIS, and DS Wizard fitted perfectly into this with its API, standardized data model, configurable templates and SSO support. There is now an automated workflow in place, to help researchers getting started with data management planning, while controlling the quality of the metadata and connecting to other services and stakeholders, such as the data protection office. This has not only helped our researchers, by lowering the barriers, but also created a good foundation for building better services in the future, with integrations, high quality metadata and better user experiences for everyone involved.

Urban Andersson, Chalmers Data Office (CDO), Chalmers University of Technology, Gothenburg

Chalmers University of Technology
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Translate DSW

You can easily contribute just by providing your language skills and help us translate DSW to various languages as well as maintain such translations. We support our community of translators that is helping us to:

  • Translate UI of DSW (messages visible in the web browser).
  • Translate document templates.

We support translation through the service localize.ds-wizard.org and directly using gettext-based translation tools (e.g. Poedit). The DSW team then manages the release process and all technical stuff as well as keeping the community standard (e.g. making sure that all contributors are credited properly in the metadata). For instance, you can check the locales for UI in the DSW Registry and on our GitHub.

No technical knowledge is required, you just need to know the language and the basics of DSW. If you want to join the community, please let us know via info@ds-wizard.org or on our Discord . We are looking forward to having you on board!

Translate DSW Illustration
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\ No newline at end of file +Translate DSW | Data Stewardship Wizard
DSW
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DSW
Get Started

Translate DSW

You can easily contribute just by providing your language skills and help us translate DSW to various languages as well as maintain such translations. We support our community of translators that is helping us to:

  • Translate UI of DSW (messages visible in the web browser).
  • Translate document templates.

We support translation through the service localize.ds-wizard.org and directly using gettext-based translation tools (e.g. Poedit). The DSW team then manages the release process and all technical stuff as well as keeping the community standard (e.g. making sure that all contributors are credited properly in the metadata). For instance, you can check the locales for UI in the DSW Registry and on our GitHub.

No technical knowledge is required, you just need to know the language and the basics of DSW. If you want to join the community, please let us know via info@ds-wizard.org or on our Discord . We are looking forward to having you on board!

Translate DSW Illustration
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\ No newline at end of file diff --git a/university.html b/university.html index 5622289..2f68825 100644 --- a/university.html +++ b/university.html @@ -1 +1 @@ -University | Data Stewardship Wizard
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University

Universities and other research institutions need to support their scientific staff also in management data – precious outputs and inputs of research activities. The Data Stewardship Wizard is ready to help and provides multiple ways of customizations to fit the institutional environment.

Universities Illustration

(Re-)Use Knowledge Models

The research project procedures, available infrastructure, and various policies may be unique to a particular research institution. This highly affects what questions the researchers need to consider to plan data management for their projects properly. The Data Stewardship Wizard allows the creation of new knowledge models from scratch and the re-use of existing ones by changing certain parts of them.

For example, a university may customize an existing knowledge model by adding questions related to local data repositories. Similarly, questions that are not relevant to the organization may be removed.

Learn More

Guide Researchers towards DMPs

By adjusting the knowledge model with institute-related questions and guides, researchers will learn and better understand the importance of data management. In addition, provided references to additional resources, contacts to local experts, exemplary plans, and answer suggestions from controlled vocabularies will promote data management in the institution.

The researchers will gain a new competence, and creating a data management plan will benefit them and the institution instead of a burden necessary for a grant application. Moreover, the Data Stewardship Wizard can become a place to share experience and continually improve local data management.

Learn More

Manage Templates

Just as funders specify DMP templates, a research institution can do the same for internal purposes. With other tools, it would be an additional burden. However, in the Data Stewardship Wizard, the users do not have to fill in answers again for a different template. Instead, they simply generate documents using various templates from the same project.

A research institute can develop customized templates, e.g., for internal project reporting and assessments. A researcher can then use this template when reporting to the institute and switch to the funders template (e.g. H2020 or Science Europe) when applying for a grant.

Learn More

Integrate with Workflows

Every research institution runs various systems to make the lives of researchers easier – local secured repository, single sign-on service, project management systems, and many others. The Data Stewardship Wizard can be adapted through multiple forms of integrations and become part of the institutional infrastructure.

For example, researchers may log in to DSW through a local identity provider, fill DMP with suggestions from the API of a partner institution, and then submit the DMP directly in DSW for review by a local data steward. Similarly, a data steward can run a customized evaluation of all projects by using DSW API.

Learn More

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To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file +University | Data Stewardship Wizard
DSW
Get Started
DSW
Get Started

University

Universities and other research institutions need to support their scientific staff also in management data – precious outputs and inputs of research activities. The Data Stewardship Wizard is ready to help and provides multiple ways of customizations to fit the institutional environment.

Universities Illustration

(Re-)Use Knowledge Models

The research project procedures, available infrastructure, and various policies may be unique to a particular research institution. This highly affects what questions the researchers need to consider to plan data management for their projects properly. The Data Stewardship Wizard allows the creation of new knowledge models from scratch and the re-use of existing ones by changing certain parts of them.

For example, a university may customize an existing knowledge model by adding questions related to local data repositories. Similarly, questions that are not relevant to the organization may be removed.

Learn More

Guide Researchers towards DMPs

By adjusting the knowledge model with institute-related questions and guides, researchers will learn and better understand the importance of data management. In addition, provided references to additional resources, contacts to local experts, exemplary plans, and answer suggestions from controlled vocabularies will promote data management in the institution.

The researchers will gain a new competence, and creating a data management plan will benefit them and the institution instead of a burden necessary for a grant application. Moreover, the Data Stewardship Wizard can become a place to share experience and continually improve local data management.

Learn More

Manage Templates

Just as funders specify DMP templates, a research institution can do the same for internal purposes. With other tools, it would be an additional burden. However, in the Data Stewardship Wizard, the users do not have to fill in answers again for a different template. Instead, they simply generate documents using various templates from the same project.

A research institute can develop customized templates, e.g., for internal project reporting and assessments. A researcher can then use this template when reporting to the institute and switch to the funders template (e.g. H2020 or Science Europe) when applying for a grant.

Learn More

Integrate with Workflows

Every research institution runs various systems to make the lives of researchers easier – local secured repository, single sign-on service, project management systems, and many others. The Data Stewardship Wizard can be adapted through multiple forms of integrations and become part of the institutional infrastructure.

For example, researchers may log in to DSW through a local identity provider, fill DMP with suggestions from the API of a partner institution, and then submit the DMP directly in DSW for review by a local data steward. Similarly, a data steward can run a customized evaluation of all projects by using DSW API.

Learn More

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To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file diff --git a/video-tutorials.html b/video-tutorials.html index 371cbbb..7cb824d 100644 --- a/video-tutorials.html +++ b/video-tutorials.html @@ -1 +1 @@ -Video Tutorials | Data Stewardship Wizard
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Video Tutorials

Learn about Data Stewardship Wizard by watching videos from past workshops, webinars, and presentations.

Video Tutorials Illustration
Data Stewardship Wizard Essentials
Data Stewardship Wizard EssentialsThis set of videos showcases the essential workflows of Researcher while working with Data Stewardship Wizard.April 2023
ELIXIR CZ Friday Coffee #5: Data Management with Data Stewardship Wizard
ELIXIR CZ Friday Coffee #5: Data Management with Data Stewardship WizardTereza Machačová9 March 2021
Data Stewardship Wizard: Introduction (Czech only)
Data Stewardship Wizard: Introduction (Czech only)Marek Suchánek3 February 2021
A Gentle Introduction to DSW for Convergers
A Gentle Introduction to DSW for ConvergersJan Slifka12 January 2021
DSW Template Development Kit: The Tutorial
DSW Template Development Kit: The TutorialMarek Suchánek19 November 2020
Data Stewardship Wizard Workshop
Data Stewardship Wizard WorkshopJan Slifka26 February 2020
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To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
\ No newline at end of file +Video Tutorials | Data Stewardship Wizard
DSW
Get Started
DSW
Get Started

Video Tutorials

Learn about Data Stewardship Wizard by watching videos from past workshops, webinars, and presentations.

Video Tutorials Illustration
Data Stewardship Wizard Essentials
Data Stewardship Wizard EssentialsThis set of videos showcases the essential workflows of Researcher while working with Data Stewardship Wizard.April 2023
ELIXIR CZ Friday Coffee #5: Data Management with Data Stewardship Wizard
ELIXIR CZ Friday Coffee #5: Data Management with Data Stewardship WizardTereza Machačová9 March 2021
Data Stewardship Wizard: Introduction (Czech only)
Data Stewardship Wizard: Introduction (Czech only)Marek Suchánek3 February 2021
A Gentle Introduction to DSW for Convergers
A Gentle Introduction to DSW for ConvergersJan Slifka12 January 2021
DSW Template Development Kit: The Tutorial
DSW Template Development Kit: The TutorialMarek Suchánek19 November 2020
Data Stewardship Wizard Workshop
Data Stewardship Wizard WorkshopJan Slifka26 February 2020
Privacy & Cookies: This site uses cookies. By continuing to use this website, you agree to their use.
To find out more, including how to control cookies, see here: Cookie Policy
Close and Accept
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