Do you need to compare questionnaire data across studies? Are the items inconsistent, or are there different versions of the same questionnaire floating around? Do you have questionnaires written in different languages that you would like to compare?
Harmony is a data harmonisation project that using Natural Language Processing to to help researchers to 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, the Centre for Longitudinal Studies at UCL and Universidade Federal de Santa Maria in Brazil, and Fast Data Science Ltd.
Harmonise questionnaire items
Harmony is a data harmonisation project that uses Natural Language Processing (NLP) to help researchers make better use of existing data from different studies. It can be used to compare questionnaire data across studies, even if the questionnaires are written in different languages.
Harmony first extracts the questions from each questionnaire. It then uses NLP techniques to compare the questions and identify their semantic similarity. This allows Harmony to match questions from different questionnaires, even if they are not worded identically.
To use Harmony, you first need to upload the questionnaires you want to compare to the Harmony website. You can upload PDF or Excel files. Harmony will then automatically extract the questions from the files and start matching them.
You can then review the matches that Harmony has made. If you disagree with a match, you can easily remove it. You can also adjust the sensitivity of the matching algorithm to make it more or less strict.
Once you are satisfied with the matches, you can export the harmonised data to Excel.
Harmony can help you to:
To learn more about Harmony, visit the Harmony website: https://harmonydata.ac.uk
You can also watch video tutorials on how to use Harmony: https://harmonydata.ac.uk/videos/
Fast Data Science is a company that develops data science tools and solutions for researchers. We developed the AI backend behind Harmony and we are committed to making data science more accessible and user-friendly.
To learn more about Fast Data Science, visit our website: https://fastdatascience.com
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Many companies and organisations have large datasets that are stored in a very unstructured format. For example, you could work for a US based healthcare provider or insurer and have patient records stored in a free text format such as HL7 files or PDFs. A building regulator, land registry, or mortgage provider may have texts and accompanying diagrams from thousands of building inspections or land title deeds. A patent attorney’s office may have records of patent applications in PDF format.
On 20 May, I attended the Expert Witness Conference in Dublin, Ireland, organised by La Touche Training. It was an eye opening event with a mixture of lawyers and expert witnesses in different fields from Ireland and abroad. The event was chaired by Mr Justice Michael Peart, with a keynote address by the Honourable Mr Justice David Barniville, President of the High Court of Ireland.
Fast Data Science at Ireland’s Expert Witness Conference on 20 May 2026 in Dublin Links to guidance on legal AI issued by legal authorities and other organisations Official guidance UK: Artificial Intelligence (AI) Guidance for Judicial Office Holders, 31 October 2025. https://www.judiciary.uk/wp-content/uploads/2025/10/Artificial-Intelligence-AI-Guidance-for-Judicial-Office-Holders-2.pdf
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