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      Fresh takes on five health data sharing domains: Quality, privacy, equity, incentives, and sustainability

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          Abstract

          As entities around the world invest in repositories and other infrastructure to facilitate health data sharing, scalable solutions to data sharing challenges are needed. We conducted semi-structured interviews with 24 experts to explore views on potential issues and policy options related to health data sharing. In this Perspective, we describe and contextualize unconventional insights shared by our interviewees relevant to issues in five domains: data quality, privacy, equity, incentives, and sustainability. These insights question a focus on granular quality metrics for gatekeeping; challenge enthusiasm for maximalist risk disclosure practices; call attention to power dynamics that potentially compromise the patient's voice; encourage faith in the sharing proclivities of new generations of scientists; and endorse accounting for personal disposition in the selection of long-term partners. We consider the merits of each insight with the broad goal of encouraging creative thinking to address data sharing challenges.

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          Most cited references25

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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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            Privacy and human behavior in the age of information.

            This Review summarizes and draws connections between diverse streams of empirical research on privacy behavior. We use three themes to connect insights from social and behavioral sciences: people's uncertainty about the consequences of privacy-related behaviors and their own preferences over those consequences; the context-dependence of people's concern, or lack thereof, about privacy; and the degree to which privacy concerns are malleable—manipulable by commercial and governmental interests. Organizing our discussion by these themes, we offer observations concerning the role of public policy in the protection of privacy in the information age.
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              Beyond Accuracy: What Data Quality Means to Data Consumers

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                Author and article information

                Contributors
                Journal
                Front Big Data
                Front Big Data
                Front. Big Data
                Frontiers in Big Data
                Frontiers Media S.A.
                2624-909X
                06 February 2023
                2023
                : 6
                : 1095119
                Affiliations
                [1] 1Center for Medical Ethics and Health Policy, Baylor College of Medicine , Houston, TX, United States
                [2] 2Consortium for Science, Policy & Outcomes, Arizona State University , Washington, DC, United States
                Author notes

                Edited by: João Valente Cordeiro, New University of Lisbon, Portugal

                Reviewed by: Rob Hooft, Dutch Techcentre for Life Sciences, Netherlands; Ricardo Cartes-Velásquez, Universidad de Concepción School of Medicine, Chile

                *Correspondence: Christi J. Guerrini ✉ guerrini@ 123456bcm.edu

                This article was submitted to Medicine and Public Health, a section of the journal Frontiers in Big Data

                †These authors share first authorship

                Article
                10.3389/fdata.2023.1095119
                9939819
                a5425822-ef30-4d72-becb-4e095209dd62
                Copyright © 2023 Guerrini, Majumder, Robinson, Cook-Deegan, Blank, Bollinger, Geary, Gutierrez, Shrikant and McGuire.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 10 November 2022
                : 16 January 2023
                Page count
                Figures: 0, Tables: 2, Equations: 0, References: 25, Pages: 6, Words: 4383
                Funding
                Funded by: National Institutes of Health, doi 10.13039/100000002;
                This research was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01 CA237118.
                Categories
                Big Data
                Perspective

                data sharing,data quality,ethics,data privacy,data archives
                data sharing, data quality, ethics, data privacy, data archives

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