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

Jonathan Lawson¹, Moran N Cabili¹, Giselle Kerry², Tiffany Boughtwood³, Adrian Thorogood^{4

5}, Pinar Alper⁵, Sarion R Bowers⁶, Rebecca R Boyles⁷, Anthony J Brookes⁸, Matthew Brush⁹, Tony Burdett², Hayley Clissold⁶, Stacey Donnelly¹, Stephanie O M Dyke¹⁰, Mallory A Freeberg², Melissa A Haendel⁹, Chihiro Hata¹¹, Petr Holub¹², Francis Jeanson¹³, Aina Jene¹⁴, Minae Kawashima¹⁵, Shuichi Kawashima¹⁶, Melissa Konopko¹⁷, Irene Kyomugisha¹⁸, Haoyuan Li¹⁹, Mikael Linden²⁰, Laura Lyman Rodriguez²¹, Mizuki Morita²², Nicola Mulder²³, Jean Muller^{24

25}, Satoshi Nagaie²⁶, Jamal Nasir²⁷, Soichi Ogishima²⁶, Vivian Ota Wang²⁸, Laura D Paglione²⁹, Ravi N Pandya³⁰, Helen Parkinson², Anthony A Philippakis¹, Fabian Prasser³¹, Jordi Rambla¹⁴, Kathy Reinold¹, Gregory A Rushton¹, Andrea Saltzman¹, Gary Saunders¹⁷, Heidi J Sofia³², John D Spalding², Morris A Swertz³³, Ilia Tulchinsky³⁴, Esther J van Enckevort³³, Susheel Varma³⁵, Craig Voisin³⁴, Natsuko Yamamoto³⁶, Chisato Yamasaki³⁶, Lyndon Zass²³, Jaime M Guidry Auvil²⁸, Tommi H Nyrönen²⁰, Mélanie Courtot²

Affiliations

¹ Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA.
² European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Hinxton, UK.
³ Australian Genomics, Murdoch Children's Research Institute, Parkville, VIC, Australia.
⁴ Centre of Genomics and Policy, Department of Human Genetics, McGill University, Montreal, QC, Canada.
⁵ ELIXIR-Luxembourg, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.
⁶ Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
⁷ RTI International, Research Triangle Park, NC, USA.
⁸ University of Leicester, Leicester, UK.
⁹ University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
¹⁰ McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Department of Neurology & Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada.
¹¹ Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Japan.
¹² BBMRI-ERIC, AT and Masaryk University, Brno, Czech Republic.
¹³ University Health Network, Toronto, ON, Canada.
¹⁴ Centre de Regulació Genòmica (CRG), Barcelona, Spain.
¹⁵ National Bioscience Database Center, Japan Science and Technology Agency, Tokyo, Japan.
¹⁶ Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Japan.
¹⁷ ELIXIR Hub, Wellcome Genome Campus, Hinxton, UK.
¹⁸ Division of Human Genetics, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
¹⁹ Canada's Michael Smith Genome Sciences Centre, Vancouver, BC, Canada.
²⁰ ELIXIR-Finland, CSC - IT Center for Science Ltd, Espoo, Finland.
²¹ Patient-Centered Outcomes Research Institute, Washington, DC, USA.
²² Okayama University, Okayama, Japan.
²³ Computational Biology Division, IDM, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
²⁴ Laboratoire de Génétique Médicale, Institut de Génétique Médicale d'Alsace, INSERM U1112, Université; de Strasbourg, Strasbourg, France.
²⁵ Laboratoire de Diagnostic Génétique, Institut de Génétique Médicale d'Alsace, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.
²⁶ Tohoku Medical Megabank Organization (ToMMo), Tohoku University, Sendai, Japan.
²⁷ Department of Life Sciences, University of Northampton, Northampton, UK.
²⁸ Office of Data Sharing, National Cancer Institute, NIH, Rockville, MD, USA.
²⁹ Spherical Cow Group, Rego Park, NY 11374, USA.
³⁰ Microsoft Research, Redmond, WA 98052, USA.
³¹ Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
³² National Human Genome Research Institute, NIH, Bethesda, MD, USA.
³³ Genomics Coordination Center, Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
³⁴ Google Cloud, Kitchener, ON N2H 5G5, Canada.
³⁵ Health Data Research UK, Gibbs Building, 215 Euston Road, London NW1 2BE, UK.
³⁶ Osaka University, Osaka, Japan.

PMID: 34820659
PMCID: PMC8591903
DOI: 10.1016/j.xgen.2021.100028

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

Jonathan Lawson et al. Cell Genom. 2021.

. 2021 Nov 10;1(2):None.

doi: 10.1016/j.xgen.2021.100028.

Authors

Affiliations

¹ Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA.
² European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Hinxton, UK.
³ Australian Genomics, Murdoch Children's Research Institute, Parkville, VIC, Australia.
⁴ Centre of Genomics and Policy, Department of Human Genetics, McGill University, Montreal, QC, Canada.
⁵ ELIXIR-Luxembourg, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.
⁶ Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
⁷ RTI International, Research Triangle Park, NC, USA.
⁸ University of Leicester, Leicester, UK.
⁹ University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
¹⁰ McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Department of Neurology & Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada.
¹¹ Bioinformation and DDBJ Center, National Institute of Genetics, Mishima, Japan.
¹² BBMRI-ERIC, AT and Masaryk University, Brno, Czech Republic.
¹³ University Health Network, Toronto, ON, Canada.
¹⁴ Centre de Regulació Genòmica (CRG), Barcelona, Spain.
¹⁵ National Bioscience Database Center, Japan Science and Technology Agency, Tokyo, Japan.
¹⁶ Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Japan.
¹⁷ ELIXIR Hub, Wellcome Genome Campus, Hinxton, UK.
¹⁸ Division of Human Genetics, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
¹⁹ Canada's Michael Smith Genome Sciences Centre, Vancouver, BC, Canada.
²⁰ ELIXIR-Finland, CSC - IT Center for Science Ltd, Espoo, Finland.
²¹ Patient-Centered Outcomes Research Institute, Washington, DC, USA.
²² Okayama University, Okayama, Japan.
²³ Computational Biology Division, IDM, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
²⁴ Laboratoire de Génétique Médicale, Institut de Génétique Médicale d'Alsace, INSERM U1112, Université; de Strasbourg, Strasbourg, France.
²⁵ Laboratoire de Diagnostic Génétique, Institut de Génétique Médicale d'Alsace, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.
²⁶ Tohoku Medical Megabank Organization (ToMMo), Tohoku University, Sendai, Japan.
²⁷ Department of Life Sciences, University of Northampton, Northampton, UK.
²⁸ Office of Data Sharing, National Cancer Institute, NIH, Rockville, MD, USA.
²⁹ Spherical Cow Group, Rego Park, NY 11374, USA.
³⁰ Microsoft Research, Redmond, WA 98052, USA.
³¹ Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
³² National Human Genome Research Institute, NIH, Bethesda, MD, USA.
³³ Genomics Coordination Center, Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
³⁴ Google Cloud, Kitchener, ON N2H 5G5, Canada.
³⁵ Health Data Research UK, Gibbs Building, 215 Euston Road, London NW1 2BE, UK.
³⁶ Osaka University, Osaka, Japan.

PMID: 34820659
PMCID: PMC8591903
DOI: 10.1016/j.xgen.2021.100028

Abstract

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.

Keywords: FAIR; GA4GH; automated data access; consent; controlled access; data access; data restrictions; ontology; secondary data use; standard.

PubMed Disclaimer

Conflict of interest statement

M.N.C. is an employee of Foundation Medicine and equity holder of Roche. A.A.P. is a venture partner at GV and an employee of alphabet corporation. He has received funding from MSFT, Verily, IBM, Intel, Bayer, and Novartis. The views expressed by L.L.R. are the author’s own and do not necessarily represent those of her organization.

Figures

**Figure 1**
Data Use Ontology permissions and modifiers DUO is a hierarchical vocabulary of data use terms most often used to denote secondary usage conditions for controlled access datasets. DUO does not aim to represent all possible data use terms, consent phrases, or complex logical permutations of permissions, limitations, or requirements. As of June 2021, DUO contains 25 terms representing two types of data use terms, permissions and modifiers. Permissions such as General Research Use (GRU), Health or Medical or Biomedical use (HMB), Disease Specific research (DS), and Population Origins and Ancestry research (POA) standardize allowed usage of the datasets. Modifiers are used to further qualify main categories of controlled access.

**Figure 2**
Browsing the Data Use Ontology The DUO OWL file has been loaded in human-friendly browsers such as the Ontology Lookup Service (OLS). This enables interactive navigation through the hierarchy and display of additional properties such as definition, comment, or relations to other terms. For example, the “disease specific research” DUO term, http://purl.obolibrary.org/obo/DUO_0000007, clarifies that it should be used in conjunction with a term from a disease ontology. The “Preferred root terms” button (middle, active green checkbox) guides display of the top classes to be displayed to the user instead of presenting the complex upper-level BFO hierarchy (accessible by selecting “All terms”)

**Figure 3**
Current implementations of the Data Use Ontology DUO has been implemented to annotate genomics datasets worldwide. As of November 2021, implementers include repositories, databases, and projects in North America, Europe, Africa, Europe, Asia, and Australia.

See this image and copyright information in PMC

References

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

Affiliations

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

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Grants and funding

LinkOut - more resources

Full Text Sources