Transform to Open Science (TOPS) OpenCore Modules Objectives and Outlines

OpenCore modules objectives and outlines developed during the curriculum sprint.

Learning Objectives

1. Ethos of Open Science
2. Open Data
3. Open Software
4. Open Results
5. Open Tools and Resources

Lesson Outlines

1. Ethos of Open Science
2. Open Data
3. Open Software
4. Open Results
5. Open Tools and Resources

Ethos of Open Science - Learning Objectives

1. Explain why responsible Open Science matters to specific research projects, science writ large, and society;
2. Explain the advantages and challenges of responsible Open Science
3. Select Open Science communities that are compatible with a research project
4. Explain how Open Science is critical for building public trust in science and influencing key societal challenges
5. Describe the key components and behaviors of responsible Open Science
6. Identify areas of concern in research that responsible Open Science can address.
7. Include stakeholders who will benefit from research done with responsible Open Science
8. Select responsible Open Science workflows

Open Data - Learning Objectives

1. Describe key characteristics of open data
2. Categorize types of open data
3. Communicate the benefits of Open data and its effects on science
4. Communicate best practices for responsibly sharing data
5. Explain the relationship between FAIR, CARE and Open Data
6. Describe key features for effective data management planning
7. Describe best practices for sharing open data

Open Software - Learning Objectives

1. Explain the benefits and challenges that producing open software encompasses.
2. Be able to identify resources for Open Software relevant for a scientific field.
3. Identify key markers of open software in code
4. How to cite others’ software in publications
5. Differentiate open, reproducible, and executable code
6. Publish software openly so others may access, use, and grow the software

Open Results - Learning Objectives

1. Identify research stages and elements of research objects that can be considered results
2. Identify the guiding practices and principles related to open results and the advantages of implementing them across stages of a research process
3. Apply open result principles to new and ongoing research projects
4. Identify paths for publicly communicating results
5. Create open results contributor guidelines and opportunities for open and equitable collaborations
6. Give credit to contributors in open results
7. Contribute and provide constructive feedback to others’ results

Open Tools and Resources - Learning Objectives

1. Explain why open science tools encourage responsible open science (e.g., using the FAIR and CARE principles)
2. Identify Open Science communities and initiatives - within and across disciplines - and join a community of practice (CoP) of interest to you
3. Provide examples of how open science is practiced in a research team
4. Identify types of Open Science tools along with their purpose
5. Match appropriate open science tools to specific objectives within the research workflow
6. Describe 3-5 open science tools and how to use them in projects (e.g., for communication, sharing of results, giving credit, and collaboration)

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Open Science Ethos - Lesson Outline

Lesson 1: WHAT: Intro to Open Science: What is it and what does it promote?

1. Introduction
2. Context and Definition
3. Definitions of Open Science and Responsible Open Science
4. Open Science aspects
5. There is no one ethos
6. Performing open science responsibly
7. Summary
8. Further Reading

Lesson 2: WHY: Benefits and Challenges of Responsible Open Science: Why does it matter?

1. Introduction
2. Iof Open Science a. Quality of research b. Quality and diversity of scholarly communications c. Response to societal challenges d. Less unnecessary repetition is better for study participants e. Personal/career benefits
3. Challenges in Open Science a. Not everything should be open - don’t overshare without consent! b. Preparing documentation, using standards, and creating metadata takes time and effort c. Open community members don’t always agree with each other d. Case scenarios in open communities e. Cultural barriers: not everyone wants to change, and institutions often move slowly f. Legal and security considerations

Lesson 3: WHO: Stakeholders of Open Science: Who practices Responsible Open Science and for whom?

1. Introduction
2. Who performs and benefits from open science? Stakeholders partaking in open science: a. Researchers b. Public c. Policy-makers
3. How each group contributes to Open Science a. Case scenarios b. Case Scenario #1: Trend: Public —> Policy-makers c. Case Scenario #2: Officialize: Policy-makers—> Researchers/Public d. Case Scenario #3: Participate: Public —>Researchers e. Case Scenario #4: Share: Researchers —>Policy-makers/Public
4. How diverse stakeholders are included in open science:
5. Activity/exercise a. Case Scenario #1: Accessible figures and writing b. Case Scenario #2: Organizing an inclusive physical event c. Case Scenario #3: Organizing an inclusive virtual meeting and preparing in advance
6. Summary

Lesson 4: WHERE: Impact of Open Science on academia, communities and society as a whole: Where open science happens.

1. Introduction
2. Legal frameworks that affect responsible open science a. Data protection, privacy, and data sovereignty b. European case: General Data Protection regulation c. South African case: Protection of Personal Information Act (POPI Act) and Open Science d. United States case: e. Summary: Working in a global society with varied data protection laws f. Intellectual property g. Whose laws apply to my community?
3. Equity and Open Science
4. A global perspective on open science a. UNESCO on Open Science Infrastructure b. Organisation for Economic Co-operation and Development (OECD) and Open Science

Lesson 5: HOW: Open Science resources & tools: How to get started in responsible open science (doing open science responsibly)

1. Introduction a. Not an afterthought - plan for open science into the design
2. Perks of digital and internet age for responsible open science
3. Digital persistent identifiers - for objects and researchers a. ORCID: A permanent unique identifier for you, as a scientific author
4. Sharing data, and software, and getting cited: Repositories you can use
5. Intellectual property, copyright, and licensing your content so it can be reused
6. Making your work useful to others
7. Sharing and publishing your manuscript a. Public repository/Preprints b. Publishing Open Science and Open Access c. Discipline- and sector-specific nuances d. Working with physical samples and tools e. Authorship: recognizing the contributions and giving credit
8. Summary: think beforehand, design for open science, never an afterthought
9. Bonus section: Open Science Skills

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Open Data - Lesson Outline

Lesson 1: What is Open Data?

1. Introduction
2. What is Data? a. Definition of Data b. Primary (raw) Data c. Metadata
3. What is Open Data? a. Availability and Accessibility b. Reusability c. Inclusivity

Lesson 2: Benefits of Open Data

1. Introduction
2. Open Data for the greater good
3. Open data for better Open Science a. Validation b. Transparency c. Collaboration
4. Open Data to support policy change
5. Open Data in face of global emergencies
6. Open Data and public engagement (citizen science)
7. Open Data and equitable knowledge sharing

Lesson 3: Responsible Open Data

1. Introduction
2. Empowering Individuals and Communities through Open Data a. Lack of protective frameworks b. Lack of proper informed consent c. Lack of equitable participation
3. Managing Data Responsibly

Lesson 4: Principles of Data Sharing

1. Introduction
2. FAIR (Findable, Accessible, Interoperable, Reusable) a. FAIR Principles Explained b. FAIR in short
3. CARE Principles of Indigenous Data Sovereignty a. Collective Benefit b. Authority to Control c. Responsibility d. Ethics
4. Identifying principles relevant to your community or other resources for principles (e.g. Environmental Justice).

Lesson 5: Planning for Open Data

1. The Data Life Cycle
2. Data Management Plans (DMP)
3. Documenting your Data (Metadata)
4. Help a. Research Communities (international and national) b. Open Science related communities c. Tools and resources d. Local Library or IT Services

Lesson 6: Sharing Open Data

1. Policies for Responsible Sharing of Open Data
2. Licenses for Open Data
3. Citations and Acknowledgements
4. Repositories and Other Sharing Methods a. Domain Specific Repositories b. Institutional Repository c. National Repositories d. General Repository
5. Data Access/Data Availability Statements

Lesson 7: Finding and Using Open Data

1. Discovering data that is open and usable
2. Determining any usage restrictions
3. Mitigating access barriers

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Open Software - Lesson Outline

Lesson 1: Open software in the context of Open Science

1. Introduction
2. Open Science Principles: How they relate to software/code
3. Open Software and Open as a Spectrum a. Source Code b. Open Source Software (OSS)
4. Core Principles of Open Source Software: What research software can move towards a. Closed source software b. Transparency c. Participation d. Collaboration
5. Summary

Lesson 2: The Pros and Cons of Open Software

1. Introduction
2. Benefits of Open Science
3. Are there any disadvantages of open software - and if so, how to mitigate them? a. As a user b. As a developer
4. Summary

Lesson 3: Licensing/Ownership & DOI's

1. Introduction
2. Licenses a. Types of licenses b. How to choose a license
3. Attribution and citation a. Digital Object Identifier (DOI) b. Citing Code without a DOI c. Attribution for pieces/snippets of code d. Publishing open software in peer-reviewed journals
4. External Requirements
5. Summary

Lesson 4: Code management/Quality

1. Introduction
2. What does it mean for software/code to be of good quality? a. Good documentation b. Clean/readable code
3. Summary
4. References

Lesson 5: Maintain good code quality

1. Introduction
2. Version Control
3. Testing
4. Responsibilities after Sharing
5. Responsibilities for ongoing maintenance

Lesson 6: Contributing to existing open software

1. Introduction
2. Benefits of contributing to an open software
3. Types of contribution to open software a. Add new features b. Fix bugs/issues c. Report issues/ suggestions about improving code d. Improving and contributing to documentation e. Create tutorials, use cases, or visuals f. Improve layout, automatization, structure of code g. Organize/attend a meetup/community building h. Code review i. Help organizing funding and support for the project
4. How to contribute a. Contributing via version control system b. Type of Commits c. Branching and Merging d. Merge conflicts
5. Recommended Practices
6. Naming Etiquette
7. Ethical Considerations
8. Summary

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Open Results - Lesson Outline

Lesson 1: The Research Process and Its Results

1. What are the different stages of the research process?
2. Define “digital research objects” and provide examples

Lesson 2: Results in the Context of Open Science

1. What are the advantages of making results open throughout the research process?
2. What resources are available to help make results open?
3. What are the guiding principles to turn a research result into an open result?

Lesson 3: Applying Open Result Framework to your Research

1. How to apply an open framework across different research objects
2. How to share your results, and selecting **tools **that support open science?
3. Using a checklist to achieve open results

Lesson 4: Providing Equitable Opportunities and Credit for Contributors to Results

1. How to define contributors to each digital research object and determine their suitable form of recognition?
2. How to create contributor guidelines that ensure equity, access, inclusion, diversity
3. How to ensure your open results are properly attributed and cited by others

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Open Tools - Lesson Outline

Lesson 1: Introduction to Open Science tools

1. Definition: What do we mean by “Open Science tools”?
2. What’s the difference between ‘open’ and ‘closed’ tools? Why use Open Science tools?
3. How do Open Science tools fit into the research lifecycle?
4. How do Open Science tools address responsible practices

Lesson 2: Open Science tools across the research lifecycle

1. Open Science tools for protocols
2. Open Science tools for data a. Sharing data with your (research) team b. Data repositories
3. Open Science tools for code a. Collaborative development tools b. Code repositories
4. Open Science tools for results
5. Open Science tools for authoring a. Collaborative writing tools b. Reference management tools c. Publishing Open Science and Open Access

Lesson 3: Open Science tools for reproducibility

1. What is reproducibility?
2. Computational notebooks a. Jupyter b. R Markdown c. Quarto

Lesson 4: Open Science communities

1. Why engage with Open Science communities?
2. What is a Community of Practice (CoP)? a. Communities list
3. How to engage with Open Science communities a. Pathways for contribution b. Pathways for collaboration c. Pathways for engagement
4. How to build and lead a community a. Guidelines for building communities b. Mountain of engagement