The Data Use Ontology to streamline responsible access to human biomedical datasets

• Published in: Cell genomics Vol. 1; no. 2; p. None
• Main Authors: Lawson, Jonathan, Cabili, Moran N., Kerry, Giselle, Boughtwood, Tiffany, Thorogood, Adrian, Alper, Pinar, Bowers, Sarion R., Boyles, Rebecca R., Brookes, Anthony J., Brush, Matthew, Burdett, Tony, Clissold, Hayley, Donnelly, Stacey, Dyke, Stephanie O.M., Freeberg, Mallory A., Haendel, Melissa A., Hata, Chihiro, Holub, Petr, Jeanson, Francis, Jene, Aina, Kawashima, Minae, Kawashima, Shuichi, Konopko, Melissa, Kyomugisha, Irene, Li, Haoyuan, Linden, Mikael, Rodriguez, Laura Lyman, Morita, Mizuki, Mulder, Nicola, Muller, Jean, Nagaie, Satoshi, Nasir, Jamal, Ogishima, Soichi, Ota Wang, Vivian, Paglione, Laura D., Pandya, Ravi N., Parkinson, Helen, Philippakis, Anthony A., Prasser, Fabian, Rambla, Jordi, Reinold, Kathy, Rushton, Gregory A., Saltzman, Andrea, Saunders, Gary, Sofia, Heidi J., Spalding, John D., Swertz, Morris A., Tulchinsky, Ilia, van Enckevort, Esther J., Varma, Susheel, Voisin, Craig, Yamamoto, Natsuko, Yamasaki, Chisato, Zass, Lyndon, Guidry Auvil, Jaime M., Nyrönen, Tommi H., Courtot, Mélanie
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 10.11.2021; Elsevier; Elsevier, Inc
• Subjects: automated data access; consent; controlled access; data access; data restrictions; FAIR; GA4GH; Genetics; Life Sciences; ontology; secondary data use; Technology; standard; FAIR; controlled access; secondary data use; data access; data restrictions; consent; automated data access; GA4GH; ontology
• ISSN: 2666-979X; 2666-979X
• DOI: 10.1016/j.xgen.2021.100028

Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset’s allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers’ discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide. [Display omitted] Biomedical advances depend on the efficient and compliant re-use of sensitive human dataThe Data Use Ontology standardizes terms and definitions for consented data usesThe Data Use Ontology facilitates discovery of, request for, and access to datasetsOver 200,000 datasets worldwide have been annotated using the Data Use Ontology The GA4GH Data Use Ontology (DUO) provides unambiguous, machine-readable standard language for consent forms and the data sharing policies they represent. Lawson et al. describe the DUO standard and implementations throughout the data access workflow to expedite data access while maintaining or improving compliant processes.