{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T12:02:05Z","timestamp":1753876925945,"version":"3.41.2"},"reference-count":24,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T00:00:00Z","timestamp":1665964800000},"content-version":"vor","delay-in-days":289,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006235","name":"Lawrence Berkeley National Laboratory","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006235","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000015","name":"U.S. Department of Energy","doi-asserted-by":"publisher","award":["DE-AC02-05CH11231"],"award-info":[{"award-number":["DE-AC02-05CH11231"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Many organizations face challenges in managing and analyzing data, especially when relevant datasets arise from multiple sources and methods. Analyzing heterogeneous datasets and additional derived data requires rigorous tracking of their interrelationships and provenance. This task has long been a Grand Challenge of data science and has more recently been formalized in the FAIR principles: that all data objects be Findable, Accessible, Interoperable, and Reusable, both for machines and for people. Adherence to these principles is necessary for proper stewardship of information, for testing regulatory compliance, for measuring the efficiency of processes, and for facilitating reuse of data-analytical frameworks.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Findings<\/jats:title>\n                  <jats:p>We present the Contextual Ontology-based Repository Analysis Library (CORAL), a platform that greatly facilitates adherence to all 4 of the FAIR principles, including the especially difficult challenge of making heterogeneous datasets Interoperable and Reusable across all parts of a large, long-lasting organization. To achieve this, CORAL's data model requires that data generators extensively document the context for all data, and our tools maintain that context throughout the entire analysis pipeline. CORAL also features a web interface for data generators to upload and explore data, as well as a Jupyter notebook interface for data analysts, both backed by a common API.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>CORAL enables organizations to build FAIR data types on the fly as they are needed, avoiding the expense of bespoke data modeling. CORAL provides a uniquely powerful platform to enable integrative cross-dataset analyses, generating deeper insights than are possible using traditional analysis tools.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/gigascience\/giac089","type":"journal-article","created":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T18:35:05Z","timestamp":1666031705000},"source":"Crossref","is-referenced-by-count":3,"title":["CORAL: A framework for rigorous self-validated data modeling and integrative, reproducible data analysis"],"prefix":"10.1093","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1102-007X","authenticated-orcid":false,"given":"Pavel S","family":"Novichkov","sequence":"first","affiliation":[{"name":"Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, CA 94720,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5153-9079","authenticated-orcid":false,"given":"John-Marc","family":"Chandonia","sequence":"additional","affiliation":[{"name":"Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, CA 94720,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4999-2931","authenticated-orcid":false,"given":"Adam P","family":"Arkin","sequence":"additional","affiliation":[{"name":"Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, CA 94720,","place":["USA"]},{"name":"Department of Bioengineering, University of California , Berkeley, CA 94720,","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,10,17]]},"reference":[{"issue":"1","key":"2024111706343324800_bib1","doi-asserted-by":"crossref","first-page":"160018","DOI":"10.1038\/sdata.2016.18","article-title":"The FAIR Guiding Principles for scientific data management and stewardship","volume":"3","author":"Wilkinson","year":"2016","journal-title":"Sci Data"},{"issue":"2","key":"2024111706343324800_bib2","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1145\/358396.358400","article-title":"Relational database: a practical foundation for productivity","volume":"25","author":"Codd","year":"1982","journal-title":"Commun ACM"},{"key":"2024111706343324800_bib3","first-page":"278","article-title":"NoSQL databases: a step to database scalability in web environment","volume-title":"Proc 13th Int Conf Inf Integr Web-Based Appl Serv","author":"Pokorny","year":"2011"},{"key":"2024111706343324800_bib4","doi-asserted-by":"crossref","first-page":"1618","DOI":"10.12688\/f1000research.12344.2","article-title":"Best practice data life cycle approaches for the life sciences","volume":"6","author":"Griffin","year":"2018","journal-title":"F1000Research"},{"issue":"7604","key":"2024111706343324800_bib5","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1038\/533452a","article-title":"1,500 scientists lift the lid on reproducibility","volume":"533","author":"Baker","year":"2016","journal-title":"Nat News"},{"year":"2018","key":"2024111706343324800_bib6"},{"issue":"6","key":"2024111706343324800_bib7","doi-asserted-by":"crossref","first-page":"e1002165","DOI":"10.1371\/journal.pbio.1002165","article-title":"The economics of reproducibility in preclinical research","volume":"13","author":"Freedman","year":"2015","journal-title":"PLoS Biol"},{"issue":"7","key":"2024111706343324800_bib8","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1038\/nbt.4163","article-title":"KBase: The United States Department of Energy Systems Biology Knowledgebase","volume":"36","author":"Arkin","year":"2018","journal-title":"Nat Biotechnol"},{"issue":"8","key":"2024111706343324800_bib9","doi-asserted-by":"crossref","first-page":"R86","DOI":"10.1186\/gb-2010-11-8-r86","article-title":"Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences","volume":"11","author":"Goecks","year":"2010","journal-title":"Genome Biol"},{"issue":"1","key":"2024111706343324800_bib10","doi-asserted-by":"crossref","first-page":"10","DOI":"10.5334\/jors.148","article-title":"xarray: N-D labeled arrays and datasets in Python","volume":"5","author":"Hoyer","year":"2017","journal-title":"J Open Res Softw"},{"volume-title":"Hierarchical Data Format, Version 5","year":"1997\u20132022","author":"The HDF Group","key":"2024111706343324800_bib11"},{"journal-title":"Unidata | NetCDF. 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