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      Essential requirements for establishing and operating data trusts: practical guidance co-developed by representatives from fifteen canadian organizations and initiatives

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          Abstract

          Introduction

          Increasingly, the label “data trust” is being applied to repeatable mechanisms or approaches to sharing data in a timely, fair, safe, and equitable way. However, there is an absence of practical guidance regarding how to establish and operate a data trust.

          Aim and approach

          In December 2019, the Canadian Institute for Health Information and the Vector Institute for Artificial Intelligence convened a working meeting of 19 people representing 15 Canadian organizations/initiatives involved in data sharing, most of which focus on public sector health data. The objective was to identify essential requirements for the establishment and operation of data trusts in the Canadian context. Preliminary requirements were discussed during the meeting and then refined as authors contributed to this manuscript.

          Results

          Twelve minimum specification requirements (“min specs”) for data trusts were identified. The foundational min spec is that data trusts must meet all legal requirements, including legal authority to collect, hold or share data. In addition, there was agreement that data trusts must have (i) an accountable governing body to ensure that the data trust achieves its stated purpose and is transparent, (ii) comprehensive data management including clear processes and qualified individuals responsible for the collection, storage, access, disclosure and use of data, (iii) training and accountability requirements for all data users and (iv) ongoing public and stakeholder engagement.

          Conclusions

          Practical guidance for the establishment and operation of data trusts was articulated in the form of 12 min specs requirements. The 12 min specs are a starting point. Future work to refine and strengthen them with members of the public, companies, and additional research data stakeholders from within and outside of Canada, is recommended.

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          Most cited references56

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          The FAIR Guiding Principles for scientific data management and stewardship

          There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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            Social determinants of health inequalities.

            The gross inequalities in health that we see within and between countries present a challenge to the world. That there should be a spread of life expectancy of 48 years among countries and 20 years or more within countries is not inevitable. A burgeoning volume of research identifies social factors at the root of much of these inequalities in health. Social determinants are relevant to communicable and non-communicable disease alike. Health status, therefore, should be of concern to policy makers in every sector, not solely those involved in health policy. As a response to this global challenge, WHO is launching a Commission on Social Determinants of Health, which will review the evidence, raise societal debate, and recommend policies with the goal of improving health of the world's most vulnerable people. A major thrust of the Commission is turning public-health knowledge into political action.
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              Publics and Counterpublics

              M Warner (2002)
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                Author and article information

                Journal
                Int J Popul Data Sci
                Int J Popul Data Sci
                IJPDS
                International Journal of Population Data Science
                Swansea University
                2399-4908
                24 August 2020
                2020
                : 5
                : 1
                : 1353
                Affiliations
                [1 ]University of Toronto, Institute of Health Policy, Management and Evaluation, 155 College Street, Toronto, ON, M5T 3M6, Canada
                [2 ]Vector Institute, Suite 710, 661 University Ave, Toronto, ON, M5G 1M1, Canada
                [3 ]Health Data Research Network Canada, 01-2206 East Mall, Vancouver BC, V6T 1Z3, Canada
                [4 ]ICES, G1 06, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
                [5 ]Canadian Institute for Health Information, Suite 600, 495 Richmond Road, Ottawa, ON, K2A 4H6, Canada
                [6 ]HPC4Health, 686 Bay St. Toronto, ON, M5G 0A4, Canada
                [7 ]University Health Network, 190 Elizabeth St., Toronto, ON, M5G 2C4, Canada
                [8 ]Hospital for Sick Children, 555 University Ave, Toronto, ON, M5G 1X8, Canada
                [9 ]University of Toronto, Department of Computer Science, 214 College St, Toronto, ON, M5T 3A1, Canada
                [10 ]Compute Ontario, Suite 1140, 661 University Avenue, Toronto, ON, M5G 1M1, Canada
                [11 ]Sunnybrook Research Institute, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
                [12 ]Population Data BC, University of British Columbia, 201-2206 East Mall, Vancouver, BC, V6T 1Z3, Canada
                [13 ]UBC Centre for Health Services and Policy Research, 2206 E Mall, Vancouver, BC, V6T 1Z3, Canada
                [14 ]University of British Columbia, Faculty of Medicine, School of Population and Public Health, 2206 E Mall, Vancouver, BC, V6T 1Z3, Canada
                [15 ]MaRS Discovery District MaRS Centre, South Tower 101 College Street, Suite 100 Toronto, ON, M5G 1L7, Canada
                [16 ]McGill University, Centre of Genomics and Policy, Suite 5200, 740, avenue Dr. Penfield, Montreal, QC, H3A 0G1, Canada
                [17 ]Global Alliance for Genomics and Health, MaRS Centre, West Tower, Suite 510, 661 University Avenue, Toronto, ON, M5G 0A3, Canada
                Author notes
                [*] [* ]Corresponding author: P. Alison Paprica. alison.paprica@ 123456utoronto.ca

                Statement of conflicts of interest: No conflicts of interest were identified. Two individuals have significant involvement in commercial organizations. Brian Courtney (co-author) has employment, significant ownership, royalties, and a director position related to Conavi Medical Inc. Alexandre Le Bouthilier (acknowledged contributor) is cofounder and shareholder of Imagia.

                Article
                5:1:31 S2399490820013531
                10.23889/ijpds.v5i1.1353
                7894384
                7ab24402-94fd-4d0c-8f86-116fe99cd7c4

                This work is licenced under a Creative Commons Attribution 4.0 International License.

                History
                Categories
                Population Data Science

                data infrastructure,data governance,public engagement,data trust,data protection

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