<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Nijsse B</submitter><funding>Dutch Research Council (NWO)</funding><funding>Wageningen University</funding><pagination>giad014</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9989329</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>12</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>The life sciences are one of the biggest suppliers of scientific data. Reusing and connecting these data can uncover hidden insights and lead to new concepts. Efficient reuse of these datasets is strongly promoted when they are interlinked with a sufficient amount of machine-actionable metadata. While the FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles have been accepted by all stakeholders, in practice, there are only a limited number of easy-to-adopt implementations available that fulfill the needs of data producers.&lt;h4>Findings&lt;/h4>We developed the FAIR Data Station, a lightweight application written in Java, that aims to support researchers in managing research metadata according to the FAIR principles. It implements the ISA metadata framework</pubmed_abstract><journal>GigaScience</journal><pubmed_title>FAIR data station for lightweight metadata management and validation of omics studies.</pubmed_title><pmcid>PMC9989329</pmcid><funding_grant_id>184.035.007</funding_grant_id><pubmed_authors>Koehorst JJ</pubmed_authors><pubmed_authors>Nijsse B</pubmed_authors><pubmed_authors>Schaap PJ</pubmed_authors></additional><is_claimable>false</is_claimable><name>FAIR data station for lightweight metadata management and validation of omics studies.</name><description>&lt;h4>Background&lt;/h4>The life sciences are one of the biggest suppliers of scientific data. Reusing and connecting these data can uncover hidden insights and lead to new concepts. Efficient reuse of these datasets is strongly promoted when they are interlinked with a sufficient amount of machine-actionable metadata. While the FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles have been accepted by all stakeholders, in practice, there are only a limited number of easy-to-adopt implementations available that fulfill the needs of data producers.&lt;h4>Findings&lt;/h4>We developed the FAIR Data Station, a lightweight application written in Java, that aims to support researchers in managing research metadata according to the FAIR principles. It implements the ISA metadata framework</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Dec</publication><modification>2026-05-28T11:25:18.964Z</modification><creation>2025-02-19T03:25:58.36Z</creation></dates><accession>S-EPMC9989329</accession><cross_references><pubmed>36879493</pubmed><doi>10.1093/gigascience/giad014</doi></cross_references></HashMap>