Clean up redirects

Author: woodthom2

config.yml

@@ -72,7 +72,7 @@ languages:
       - name: User guide
         parent: Help
         weight: 20
-        url: /formatting-help/
+        url: /open-source-for-social-science/formatting-help/
       - name: Developer guide
         parent: Help
         weight: 30

content/en/_index.md

@@ -15,7 +15,7 @@ blocks:
   heading: "Harmonise questionnaire items with **Harmony**."
   subheading: Harmony is a tool for retrospective harmonisation of questionnaire items.
   copy: |-
-    Do you need to [compare questionnaire items across studies](/gad-7-vs-beck-anxiety-inventory/)? Do you want to find the best match for a set of items? Are there are different versions of the same questionnaire floating around and you want to make sure [how compatible they are](/harmonisation-validation/patient-health-questionnaire-9-phq-9/)? Are the questionnaires [written in different languages](/harmony-supports-over-8-languages/) that you would like to compare?
+    Do you need to [compare questionnaire items across studies](/compare-harmonise-instruments/gad-7-vs-beck-anxiety-inventory/)? Do you want to find the best match for a set of items? Are there are different versions of the same questionnaire floating around and you want to make sure [how compatible they are](/harmonisation-validation/patient-health-questionnaire-9-phq-9/)? Are the questionnaires [written in different languages](/psychology-ai-tool/harmony-many-languages/) that you would like to compare?
 
     The Harmony project is a data harmonisation project that uses [Natural Language Processing](https://fastdatascience.com/guide-natural-language-processing-nlp/) to help researchers make better use of existing data from different studies by supporting them with the harmonisation of various measures and items used in different studies. Harmony is a collaboration project between [Ulster University](https://ulster.ac.uk/), [University College London](https://ucl.ac.uk/), the [Universidade Federal de Santa Maria](https://www.ufsm.br/), and [Fast Data Science](http://fastdatascience.com/).  Harmony is funded by [Wellcome](https://wellcome.org/) as part of the [Wellcome Data Prize in Mental Health](https://wellcome.org/grant-funding/schemes/wellcome-mental-health-data-prize).
  
@@ -96,7 +96,7 @@ blocks:
   - text: R package on Github
     url: https://github.com/harmonydata/harmony_r
   - text: Documentation
-    url: /harmony-r-released/
+    url: /open-source-for-social-science/harmony-r-package/
   - text: Google Colab notebook
     url: "https://github.com/harmonydata/experiments/blob/main/Harmony_R_example.ipynb"
   - text: R markdown notebook for R Studio
@@ -189,7 +189,7 @@ blocks:
   copy: |
     Our tool, [Harmony](https://fastdatascience.com/harmony-wellcome-data-prize/), allows researchers to upload a set of mental health questionnaires in PDF or Excel format, such as the [GAD-7 anxiety questionnaire](https://adaa.org/sites/default/files/GAD-7_Anxiety-updated_0.pdf). It identifies which questions among questionnaires are identical, similar in meaning, or antonyms of each other, and generates a network graph. This allows researchers to harmonise datasets.
 
-    Uniquely, Harmony relies on [Transformer neural network architectures](https://deepai.org/machine-learning-glossary-and-terms/transformer-neural-network) and is not dependent on a dictionary approach or word list. This allows for [multilingual data harmonisation](/harmony-supports-over-8-languages/) (English and Portuguese are our languages of focus), and Harmony is able to correctly map the GAD-7 used in the UK to the [GAD-7 used in Brazil](https://pesquisa.bvsalud.org/portal/resource/pt/lil-788637), despite the Brazilian questionnaire being in Brazilian Portuguese.
+    Uniquely, Harmony relies on [Transformer neural network architectures](https://deepai.org/machine-learning-glossary-and-terms/transformer-neural-network) and is not dependent on a dictionary approach or word list. This allows for [multilingual data harmonisation](/psychology-ai-tool/harmony-many-languages/) (English and Portuguese are our languages of focus), and Harmony is able to correctly map the GAD-7 used in the UK to the [GAD-7 used in Brazil](https://pesquisa.bvsalud.org/portal/resource/pt/lil-788637), despite the Brazilian questionnaire being in Brazilian Portuguese.
 
     Using Harmony, our team was able to harmonise multilingual datasets and conduct groundbreaking research into social isolation and anxiety with NLP supplying a quantitative measure of the equivalence of the different mental health datasets.
 

content/en/ai-in-mental-health.md

@@ -11,7 +11,7 @@ url: "/ai-in-mental-health/"
 
 Artificial intelligence (AI) is revolutionising numerous fields, and mental health research is no exception. By harnessing the power of AI, researchers are gaining unprecedented insights into the complexities of mental health, leading to more effective interventions and treatments.
 
-One notable example of AI's impact is the development of tools like **Harmony**. This [innovative AI tool](/psychology-ai-tool/), originally funded by the Wellcome Trust as part of the [Wellcome data prize](/ai-in-mental-health/radio-podcast-about-wellcome-data-prize/) and later by UKRI, uses natural language processing (NLP) to streamline the [harmonisation of mental health questionnaires](/data-harmonisation/find-matching-and-common-items-in-questionnaires-and-surveys/). By automating this time-consuming process, Harmony enables researchers to compare data across studies more efficiently, leading to more robust and reliable [secondary data analysis](/ai-in-mental-health/ppie-for-secondary-data-analysis/).
+One notable example of AI's impact is the development of tools like **Harmony**. This [innovative AI tool](/psychology-ai-tool/), originally funded by the Wellcome Trust as part of the [Wellcome data prize](/ai-in-mental-health/radio-podcast-about-wellcome-data-prize/) and later by UKRI, uses natural language processing (NLP) to streamline the [harmonisation of mental health questionnaires](/item-harmonisation/find-matching-and-common-items-in-questionnaires-and-surveys/). By automating this time-consuming process, Harmony enables researchers to compare data across studies more efficiently, leading to more robust and reliable [secondary data analysis](/ai-in-mental-health/ppie-for-secondary-data-analysis/).
 
 
 We have recently published a paper in BMC Psychiatry validating Harmony for real-world data:  McElroy, E., Wood, T.A., Bond, R., Mulvenna M., Shevlin M., Ploubidis G., Scopel Hoffmann M., Moltrecht B., [Using natural language processing to facilitate the harmonisation of mental health questionnaires: a validation study using real-world data](/ai-in-mental-health/bmc-psychiatry-paper/). BMC Psychiatry 24, 530 (2024). https://doi.org/10.1186/s12888-024-05954-2

content/en/blog/ai-meetup.md

@@ -29,7 +29,7 @@ Date: **27 March 2024**
 
 {{< image src="/images/20240327-thomas-wood-ai-camp-harmony.jpg" alt="Thomas Wood presenting Harmony at AI Camp on 27 March 2024" title="Thomas Wood presenting Harmony at AI Camp on 27 March 2024" >}}
 
-Abstract: In this talk, Thomas will discuss [AI for social sciences research](/item-harmonisation/harmony-a-free-ai-tool-for-cross-cohort-research/) and how to build a research tool with NLP and AI with [open source tool Harmony](/how-can-i-contribute-to-an-open-source-project/), funded by [Wellcome Trust](https://wellcome.org) with [Social Finance](https://www.socialfinance.org.uk/) and developed with [Ulster University](https://ulster.ac.uk), [UCL](https://ucl.ac.uk) and [Universidade Federal de Santa Maria in Brazil](https://ufsm.br).
+Abstract: In this talk, Thomas will discuss [AI for social sciences research](/item-harmonisation/harmony-a-free-ai-tool-for-cross-cohort-research/) and how to build a research tool with NLP and AI with [open source tool Harmony](/open-source-for-social-science/), funded by [Wellcome Trust](https://wellcome.org) with [Social Finance](https://www.socialfinance.org.uk/) and developed with [Ulster University](https://ulster.ac.uk), [UCL](https://ucl.ac.uk) and [Universidade Federal de Santa Maria in Brazil](https://ufsm.br).
 
 {{< card heading="Attend" copy="Sign up on AICamp website" url="https://www.aicamp.ai/event/eventdetails/W2024032710" >}}
 
@@ -67,6 +67,6 @@ This follows on from the talk on Harmony given by Bettina Moltrecht, PhD last we
 * 8 October 2024: [Harmony: a free online tool using LLMs for research in psychology and social sciences](/psychology-ai-tool/aidl-meetup/)  at AI|DL London
 * 11 and 12 September 2024: [Harmony at MethodsCon Futures](/ai-in-mental-health/harmony-at-methodscon-futures/
 ) in Manchester
-* 2 July 2024: [Harmony: NLP and generative models for psychology research](/psychology-ai-tool/pydata-meetup/)  at Pydata London
-* 3 June 2024: [Harmony Hackathon](/hackathon/) at UCL
+* 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.

content/en/blog/aidl-meetup.md

@@ -19,7 +19,7 @@ Topic: **Harmony: a free online tool using LLMs for research in psychology and s
 
 Speaker: [Thomas Wood](https://freelancedatascientist.net/) ([Fast Data Science](https://fastdatascience.com/))
 
-Description: Thomas Wood will present our work on Harmony, harmonydata.ac.uk, which is a [free online tool](/psychology-ai-tool/) that uses generative AI and LLMs to help researchers compare items in questionnaires such as [GAD-7](/compare-harmonise-instruments/gad-7-vs-sdq/) (used to measure anxiety), even when they are [written in different languages](/nlp-semantic-text-matching/harmony-on-kufungisisa-a-cultural-concept-of-distress-from-zimbabwe/). Harmony is open source under [MIT License](https://github.com/harmonydata/harmony/blob/main/LICENSE) and is written in Python, and uses [HuggingFace Sentence Transformers](/measuring-the-performance-of-nlp-algorithms/) to find similarities between questionnaires.
+Description: Thomas Wood will present our work on Harmony, harmonydata.ac.uk, which is a [free online tool](/psychology-ai-tool/) that uses generative AI and LLMs to help researchers compare items in questionnaires such as [GAD-7](/compare-harmonise-instruments/gad-7-vs-sdq/) (used to measure anxiety), even when they are [written in different languages](/nlp-semantic-text-matching/harmony-on-kufungisisa-a-cultural-concept-of-distress-from-zimbabwe/). Harmony is open source under [MIT License](https://github.com/harmonydata/harmony/blob/main/LICENSE) and is written in Python, and uses [HuggingFace Sentence Transformers](/nlp-semantic-text-matching/measuring-the-performance-of-nlp-algorithms/) to find similarities between questionnaires.
 
 [Harmony Discovery](/discovery/) will soon allow researchers to discover datasets using a [vector search](/nlp-semantic-text-matching/how-does-harmony-work/).
 
@@ -56,7 +56,7 @@ The AI|DL AI meetup is sponsored by [Daemon](https://www.dae.mn/).
 
 07:10pm - Thomas Wood, Director of [Fast Data Science](https://fastdatascience.com/) [Project Harmony: a free online tool using LLMs for research in psychology and social sciences](https://fastdatascience.com/ai-in-research/aidl-meetup/)
 
-[Thomas Wood](https://fastdatascience.com/team/) will present our work on Harmony (harmonydata.ac.uk), which is a [free online tool](/psychology-ai-tool/) that uses generative AI and LLMs to help researchers compare items in questionnaires such as [GAD-7](https://harmonydata.ac.uk/compare-harmonise-instruments/gad-7-vs-beck-anxiety-inventory/) (used to measure [anxiety](/discover-data/anxiety-datasets-and-studies/)), even when they are written in [different languages](/nlp-semantic-text-matching/harmony-on-kufungisisa-a-cultural-concept-of-distress-from-zimbabwe/). Harmony is [open source](/how-can-i-contribute-to-an-open-source-project/) under MIT License and is written in Python, and uses [HuggingFace Sentence Transformers](/measuring-the-performance-of-nlp-algorithms/) to find similarities between questionnaires. Harmony will soon allow researchers to discover datasets using a vector search.
+[Thomas Wood](https://fastdatascience.com/team/) will present our work on Harmony (harmonydata.ac.uk), which is a [free online tool](/psychology-ai-tool/) that uses generative AI and LLMs to help researchers compare items in questionnaires such as [GAD-7](https://harmonydata.ac.uk/compare-harmonise-instruments/gad-7-vs-beck-anxiety-inventory/) (used to measure [anxiety](/discover-data/anxiety-datasets-and-studies/)), even when they are written in [different languages](/nlp-semantic-text-matching/harmony-on-kufungisisa-a-cultural-concept-of-distress-from-zimbabwe/). Harmony is [open source](/open-source-for-social-science/) under MIT License and is written in Python, and uses [HuggingFace Sentence Transformers](/nlp-semantic-text-matching/measuring-the-performance-of-nlp-algorithms/) to find similarities between questionnaires. Harmony will soon allow researchers to discover datasets using a vector search.
 
 07:50pm - Break
 
@@ -81,7 +81,7 @@ Our session will explore the transformative potential of Generative AI, focusing
 
 * 11 and 12 September 2024: [Harmony at MethodsCon Futures](/ai-in-mental-health/harmony-at-methodscon-futures/
 ) in Manchester
-* 2 July 2024: [Harmony: NLP and generative models for psychology research](/psychology-ai-tool/pydata-meetup/)  at Pydata London
-* 3 June 2024: [Harmony Hackathon](/hackathon/) at UCL
+* 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.
 * 27 March 2024: [Harmony at AI Camp](/psychology-ai-tool/aicamp-meetup/)

content/en/blog/bmc-paper.md

@@ -23,13 +23,13 @@ We are pleased to announce the publication of a paper validating Harmony on real
 
 ## Summary of the Harmony real-world validation study
 
-Our study aimed to evaluate the effectiveness of Natural Language Processing (NLP) in [harmonising mental health questionnaires](/ces-d-vs-gad-7/) for cross-study research in areas such as [mental health](/ai-in-mental-health/).
+Our study aimed to evaluate the effectiveness of Natural Language Processing (NLP) in [harmonising mental health questionnaires](/compare-harmonise-instruments/ces-d-vs-gad-7/) for cross-study research in areas such as [mental health](/ai-in-mental-health/).
 
-By comparing the semantic similarity of questionnaire items using NLP (the [Sentence-BERT transformer model](/measuring-the-performance-of-nlp-algorithms/)) with their actual correlation in a sample population, we found a moderate relationship (*r* = .48, *p* < .001) between the two measures. This suggests that NLP can accurately identify similar questions across different questionnaires. 
+By comparing the semantic similarity of questionnaire items using NLP (the [Sentence-BERT transformer model](/nlp-semantic-text-matching/measuring-the-performance-of-nlp-algorithms/)) with their actual correlation in a sample population, we found a moderate relationship (*r* = .48, *p* < .001) between the two measures. This suggests that NLP can accurately identify similar questions across different questionnaires. 
 
 While the NLP model showed promise in uncovering underlying patterns in the data, it required manual intervention to determine which relationships were truly relevant. 
 
-Our study showed that NLP can be a useful tool to match [similar questions from different questionnaires](/data-harmonisation/find-matching-and-common-items-in-questionnaires-and-surveys/), but it's not perfect and should be used with caution.
+Our study showed that NLP can be a useful tool to match [similar questions from different questionnaires](/item-harmonisation/find-matching-and-common-items-in-questionnaires-and-surveys/), but it's not perfect and should be used with caution.
 
 ## Citing the BMC validation paper
 

content/en/blog/clinical-trial-research-data-harmonisation.md

@@ -35,7 +35,7 @@ Clinical data harmonisation entails the process of integrating, standardizing, a
 Clinical data harmonisation plays a pivotal role in advancing clinical research by addressing key challenges associated with data variability and heterogeneity. The importance of clinical data harmonisation can be highlighted through various crucial aspects:
 
 1. **Facilitating Interoperability:**
-   - Clinical trials often involve collaboration among multiple institutions, each employing different data collection systems and formats. Harmonising data ensures seamless interoperability, enabling efficient integration of diverse datasets. This fosters collaboration, enhances the exchange of information, and reduces obstacles to data sharing, ultimately [contributing](/contributing-to-harmony) to a more interconnected research environment.
+   - Clinical trials often involve collaboration among multiple institutions, each employing different data collection systems and formats. Harmonising data ensures seamless interoperability, enabling efficient integration of diverse datasets. This fosters collaboration, enhances the exchange of information, and reduces obstacles to data sharing, ultimately [contributing](/open-source-for-social-science/contributing-to-harmony-nlp-project/) to a more interconnected research environment.
 
 2. **Ensuring Consistency:**
    - Standardizing data elements and definitions across trials is essential for ensuring consistency in measurements and assessments. Consistent data facilitates accurate comparisons between studies, allowing researchers to draw meaningful conclusions and make informed decisions. Without harmonisation, variations in data definitions and measurement units could lead to misinterpretations and compromises in the reliability of research outcomes.

content/en/blog/combining-multiple-survey-sources.md

@@ -13,7 +13,7 @@ url: "/data-harmonisation/combine-multiple-survey-sources-best-practices/"
 ---
 
 
-In today’s data-driven world, surveys are a pivotal tool for researchers, marketers, and decision-makers. They offer invaluable insights into consumer behavior, employee [satisfaction](/harmonisation-validation/client-satisfaction-questionnaire-csq), and wide-ranging social issues. However, the challenge often lies in harmonising data from multiple [survey](/combining-multiple-survey-sources-best-practices) sources to draw coherent, actionable conclusions. This blog explores best practices for combining survey data, inspired by cutting-edge methodologies.
+In today’s data-driven world, surveys are a pivotal tool for researchers, marketers, and decision-makers. They offer invaluable insights into consumer behavior, employee [satisfaction](/harmonisation-validation/client-satisfaction-questionnaire-csq), and wide-ranging social issues. However, the challenge often lies in harmonising data from multiple [survey](/data-harmonisation/combine-multiple-survey-sources-best-practices/) sources to draw coherent, actionable conclusions. This blog explores best practices for combining survey data, inspired by cutting-edge methodologies.
 
 ## Table of Contents
 - [Introduction](#introduction)