J 2021

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

LAWSON, Jonathan, Moran N CABILI, Giselle KERRY, Tiffany BOUGHTWOOD, Adrian THOROGOOD et. al.

Základní údaje

Originální název

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

Autoři

LAWSON, Jonathan, Moran N CABILI, Giselle KERRY, Tiffany BOUGHTWOOD, Adrian THOROGOOD, Pinar ALPER, Sarion R BOWERS, Rebecca R BOYLES, Anthony J BROOKES, Matthew BRUSH, Tony BURDETT, Hayley CLISSOLD, Stacey DONNELLY, Stephanie O M DYKE, Mallory A FREEBERG, Melissa A HAENDEL, Chihiro HATA, Petr HOLUB, Francis JEANSON, Aina JENE, Minae KAWASHIMA, Shuichi KAWASHIMA, Melissa KONOPKO, Irene KYOMUGISHA, Haoyuan LI, Mikael LINDEN, Laura Lyman RODRIGUEZ, Mizuki MORITA, Nicola MULDER, Jean MULLER, Satoshi NAGAIE, Jamal NASIR, Soichi OGISHIMA, Vivian Ota WANG, Laura D PAGLIONE, Ravi N PANDYA, Helen PARKINSON, Anthony A PHILIPPAKIS, Fabian PRASSER, Jordi RAMBLA, Kathy REINOLD, Gregory A RUSHTON, Andrea SALTZMAN, Gary SAUNDERS, Heidi J SOFIA, John D SPALDING, Morris A SWERTZ, Ilia TULCHINSKY, J ESTHER, van ENCKEVORT, Susheel VARMA, Craig VOISIN, Natsuko YAMAMOTO, Chisato YAMASAKI, Lyndon ZASS, M JAIME, Guidry AUVIL, Tommi H NYRÖNEN a Mélanie COURTOT

Vydání

Cell Genomics, 2021, 2666-979X

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Organizační jednotka

Ústav výpočetní techniky
Změněno: 28. 3. 2023 17:42, Mgr. Alena Mokrá

Anotace

V originále

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.