Improving metadata consistency in longitudinal research through controlled vocabulary realignment

Controlled vocabularies are essential for enabling FAIR (Findable, Accessible, Interoperable, Reusable) data. CLOSER Discovery – the UK’s most comprehensive research tool for longitudinal population studies (LPS) – contains question-and variable-level metadata for 13 leading UK LPS. Each question and variable in CLOSER Discovery is mapped to a topic from CLOSER’s two-level controlled vocabulary, initially developed using a combination of relevant Medical Subject Headings (MeSH) and European Language Social Sciences Thesaurus (ELSST) terms. Level one contains broad high-level topics such as Health behaviour, and level two contains more granular sub-topics such as Sleep and Smoking. Each topic has a name, code, and short description. CLOSER are currently refining our controlled vocabulary in alignment with ELSST. This involves mapping each topic to an ELSST term(s), providing comprehensive definitions and examples, removing duplicate topics, restructuring topic levels, and creating new topics where needed. These improvements aim to support more accurate and consistent topic mappings within and between studies, improving the findability and reusability of questions and variables in CLOSER Discovery. This poster will outline CLOSER’s controlled vocabulary realignment process, highlight key changes to the controlled vocabulary, and showcase our new guidance enabling users to map questions and variables to topics with greater accuracy and consistency.