Researchers within the Life Sciences and Health domain have a hard time to find, access and reuse data resources relevant to them. This project will help improve this situation and boost the transition to Open Science by making data resources more Findable, Accessible, Interoperable, Reusable (FAIR) across the Dutch LSH domain, while collaborating with existing initiatives. International alignment comes from close involvement in organisations such as ELIXIR, EOSC and RDA. We will appoint a FAIR metadata specialist and a bioinformatics/technical specialist to support alignment among LSH research initiatives and help realise a collective FAIR data environment valuable for end-users.

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The LEARN-FAIR project intends to foster cooperation and knowledge exchange among FAIR (Findable, Accessible, Interoperable, and Reusable data) trainers by establishing a Dutch FAIR Trainers Community. Additionally, the project focuses on identifying training needs for researchers and data stewards, as well as existing educational materials, in order to develop new Open Educational Resources. To ensure that these materials meet the (future) needs of the community, the LEARN-FAIR project combines empirical research with active community engagement.

Dutch long-term cohort studies monitor the health of large groups of people. They collect data differently, making combining data and doing research together difficult. This project aims make data from Dutch long-term cohort studies more comparable. We will identify core study data, harmonize with existing best practices and add it to a national standard. This makes it easier for data from new cohorts to be used together for research. We also test whether our standard can be used for existing cohort studies and for specific disease areas, such as depression and diabetes. This project contributes to better data for research.