internal links

content/en/blog/ai-meetup.md

@@ -70,3 +70,4 @@ This follows on from the talk on Harmony given by Bettina Moltrecht, PhD last we
 * 2 July 2024: [Harmony: NLP and generative models for psychology research](/open-source-for-social-science/pydata-meetup/)  at Pydata London
 * 3 June 2024: [Harmony Hackathon](/open-source-for-social-science/hackathon/) at UCL
 * 5 May 2024: [Harmony: A global platform for harmonisation, translation and cooperation in mental health](/ai-in-mental-health/harmony-at-lifecourse-seminar/) at  Melbourne Children’s LifeCourse Initiative seminar series.
+* 17 August 2023: [Harmony and TIDAL workshop](/ai-in-mental-health/harmony-and-tidal-workshop)

content/en/blog/aidl-meetup.md

@@ -85,3 +85,4 @@ Our session will explore the transformative potential of Generative AI, focusing
 * 3 June 2024: [Harmony Hackathon](/open-source-for-social-science/hackathon/) at UCL
 * 5 May 2024: [Harmony: A global platform for harmonisation, translation and cooperation in mental health](/ai-in-mental-health/harmony-at-lifecourse-seminar/) at  Melbourne Children’s LifeCourse Initiative seminar series.
 * 27 March 2024: [Harmony at AI Camp](/psychology-ai-tool/aicamp-meetup/)
+* 17 August 2023: [Harmony and TIDAL workshop](/ai-in-mental-health/harmony-and-tidal-workshop)

content/en/blog/data-harmonisation-healthcare.md

@@ -44,7 +44,7 @@ Harmonisation methods in data science and healthcare research aim to standardize
 ### Ensuring Reliable Data for Algorithms
 
 #### Quality Over Quantity
-In the realm of data harmonisation, the emphasis on quality over quantity cannot be overstated. Accurate and reliable data is paramount for developing algorithms that are truly effective and can lead to meaningful insights and outcomes. The focus should be on ensuring that each data point collected and integrated into larger datasets meets a high standard of quality, as this will significantly impact the [performance](/nlp-semantic-text-matching/measuring-the-performance-of-nlp-algorithms/) of machine learning models and AI algorithms. Poor-quality data can lead to inaccurate predictions, biased outcomes, and ultimately, decisions that may not be in the best interest of patients or research objectives.
+In the realm of data harmonisation, the emphasis on quality over quantity cannot be overstated. Accurate and reliable data is paramount for developing algorithms that are truly effective and can lead to meaningful insights and outcomes. The focus should be on ensuring that each data point collected and integrated into larger datasets meets a high standard of quality, as this will significantly impact the [performance](/nlp-semantic-text-matching/measuring-the-performance-of-nlp-algorithms/) of machine learning models and [AI algorithms and tools](/psychology-ai-tool/). Poor-quality data can lead to inaccurate predictions, biased outcomes, and ultimately, decisions that may not be in the best interest of patients or research objectives.
 
 
 #### Role of Machine Learning and AI

content/en/blog/harmonised-data.md

@@ -166,7 +166,7 @@ Rarely will you come across a business whose customers, partners, audience, or e
 
 Using contact information alone, for example, transliteration must consider both cultural and regional differences in how names as well as addresses might be entered, formatted and organised – while maintaining the highest level of accuracy which anyone, irrespective of their region or language, can trust.
 
-With businesses entering and re-entering an increasing number of records across their systems, a fail-proof way must exist to ensure that the data entered is matched as accurately and correctly as possible. So, unless there’s a proper data harmonisation tool or app in place, organisations will find it very hard, almost impossible, in fact, to obtain and maintain a centralised data governance strategy – because varying insights as well as values will be generated for the very same standard of data across different sources.
+With businesses entering and re-entering an increasing number of records across their systems, a fail-proof way must exist to ensure that the data entered is matched as accurately and correctly as possible. So, unless there’s a proper data harmonisation tool or app in place, organisations will find it very hard, almost impossible, in fact, to obtain and maintain a centralised [data governance](/ai-in-mental-health/research-funders-ai-governance/) strategy – because varying insights as well as values will be generated for the very same standard of data across different sources.
 
 Unless there is a clear indication of which data source is the most trusted and relevant, research teams trying to make sense of multiple sources of data will find themselves dealing with the same issue: differing insights for the same data derived from different sources.
 

content/en/blog/ideas.md

@@ -284,3 +284,5 @@ These are proposals in the mailing lists and Discord which have not been publish
 * More Kaggle competitions
 
 List prepared in collaboration with [Piyush Raj](https://github.com/0x48piraj).
+
+See also: [Harmony going forward: 5 key things Implementation Science has taught us to focus on](/ai-in-mental-health/harmony-going-forward/)

content/en/blog/pydata.md

@@ -56,3 +56,4 @@ Thomas Wood will present our work on Harmony, harmonydata.ac.uk, which is a [fre
 * 3 June 2024: [Harmony Hackathon](/open-source-for-social-science/hackathon/) at UCL
 * 5 May 2024: [Harmony: A global platform for harmonisation, translation and cooperation in mental health](/ai-in-mental-health/harmony-at-lifecourse-seminar/) at  Melbourne Children’s LifeCourse Initiative seminar series.
 * 27 March 2024: [Harmony at AI Camp](/psychology-ai-tool/aicamp-meetup/)
+* 17 August 2023: [Harmony and TIDAL workshop](/ai-in-mental-health/harmony-and-tidal-workshop)

content/en/blog/radio-podcast-about-wellcome-data-prize.md

@@ -19,3 +19,5 @@ The Wellcome Data Prize was recently featured on [Smile 90.4FM](https://smilefm.
 <iframe loading="lazy" id="inlineFrameExample" title="Inline Frame Example" src="https://echocast.fabrik.fm/9qY6RR97RmW37q" width="300" height="400" style="box-sizing: inherit; border: 0px; font-size: 17px; font-style: normal; font-weight: 300; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline; max-width: 100%; color: rgb(58, 58, 58); font-family: Roboto, sans-serif; font-variant-ligatures: normal; font-variant-caps: normal; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; background-color: rgb(255, 255, 255); text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;"></iframe>
 
 {{< /htmlcode >}}
+
+See also - during the Wellcome Data Prize we participated in a [joint workshop with TIDAL, another team in the Data Prize](/ai-in-mental-health/harmony-and-tidal-workshop).

content/en/blog/research-funders-ai-governance-vacuum.md

@@ -26,4 +26,9 @@ The Harmony team has taken steps to ensure the long term viability and sustainab
 
 
 We have regularly presented the Harmony project at events such as [AI|DL London](/psychology-ai-tool/aidl-meetup/), [MethodsCon Futures in Manchester](/ai-in-mental-health/harmony-at-methodscon-futures/
-), [Hackathon in UCL](/open-source-for-social-science/hackathon/), [Melbourne Children’s LifeCourse Initiative seminar series](/ai-in-mental-health/harmony-at-lifecourse-seminar/), and [AI Camp](/psychology-ai-tool/aicamp-meetup/).
+), [Hackathon in UCL](/open-source-for-social-science/hackathon/), [Melbourne Children’s LifeCourse Initiative seminar series](/ai-in-mental-health/harmony-at-lifecourse-seminar/), and [AI Camp](/psychology-ai-tool/aicamp-meetup/).
+
+## Other news coverage
+
+* [See news coverage of the Harmony project on other websites](/ai-in-mental-health/news-coverage)
+* [Radio postcast about the Wellcome Data Prize](/ai-in-mental-health/radio-podcast-about-wellcome-data-prize)

content/en/blog/sign-up-to-test-harmony.md

@@ -6,4 +6,4 @@ categories: ["harmony"]
 image: /images/blog/Social-media-posts_LinkedIn_06.png
 ---
 
-We are running [workshops](https://harmonydata.ac.uk/harmony-tidal-workshop) to test Harmony – see the [signup link here](https://ulster.onlinesurveys.ac.uk/harmony-online-eoi).
+We are running [workshops](https://harmonydata.ac.uk/harmony-tidal-workshop) to test Harmony so that we can plan [future development](/ai-in-mental-health/harmony-going-forward/) – see the [signup link here](https://ulster.onlinesurveys.ac.uk/harmony-online-eoi).

content/en/blog/sustainability.md

@@ -13,7 +13,7 @@ url: "/open-source-for-social-science/sustainability/"
 
 Longevity is a tricky topic in software development.
 
-We've been thinking about how we can make sure that Harmony continues to operate for a long time in the future, since Harmony is intended as a public good for researchers to use with no strings attached (an [open source tool for social science](/open-source-for-social-science/)).
+We've been thinking about how we can make sure that Harmony continues to operate for a [long time in the future](/ai-in-mental-health/harmony-going-forward/), since Harmony is intended as a public good for researchers to use with no strings attached (an [open source tool for social science](/open-source-for-social-science/)).
 
 # Sustainability assessment
 
@@ -197,7 +197,7 @@ _Question 13.3: Do you provide success stories on your website?_
 
 A great way of showing off your software is to write case studies about the people who've used it and how they've used it. This helps potential users learn about the software but, more to the point, is a great advert for your software. If you can show happy users benefiting from your software, you are likely to gain more users.
 
-_Question 13.8: If your software is developed as an open source project (and, not just a project developing open source software), do you have a governance model?_
+_Question 13.8: If your software is developed as an open source project (and, not just a project developing open source software), do you have a [governance model](/ai-in-mental-health/research-funders-ai-governance)?_
 
 A governance model sets out how a, open source project is run. It describes the roles within the project and its community and the responsibilities associated with each role; how the project supports its community; what contributions can be made to the project, how they are made, any conditions the contributions must conform to, who retains copyright of the contributions and the process followed by the project in accepting the contribution; and, the decision-making process in within the project.
 

content/en/blog/what-is-truly-harmonised-data.md

@@ -116,7 +116,7 @@ To bridge the gap between perception and reality, businesses need to:
 Begin by conducting a comprehensive assessment of your current data landscape. Identify disparate datasets, sources of data silos, and potential inconsistencies. This assessment serves as the foundation for developing a robust harmonisation strategy.
 
 - **Establishing Data Governance Policies**
-Implementing clear data governance policies is imperative for sustaining harmonised data. Define data ownership, establish quality standards, and enforce protocols for data handling and integration.
+Implementing clear [data governance policies](/ai-in-mental-health/research-funders-ai-governance) is imperative for sustaining harmonised data. Define data ownership, establish quality standards, and enforce protocols for data handling and integration.
 
 - **Utilizing Advanced Data Integration Tools**
 Investing in advanced data integration tools streamlines the harmonisation process. These tools automate data workflows, enhance interoperability, and provide real-time monitoring capabilities, ensuring continuous data harmony.