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      Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff

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          Abstract

          Background

          Significant efforts are underway within the biomedical research community to encourage sharing and reuse of research data in order to enhance research reproducibility and enable scientific discovery. While some technological challenges do exist, many of the barriers to sharing and reuse are social in nature, arising from researchers’ concerns about and attitudes toward sharing their data. In addition, clinical and basic science researchers face their own unique sets of challenges to sharing data within their communities. This study investigates these differences in experiences with and perceptions about sharing data, as well as barriers to sharing among clinical and basic science researchers.

          Methods

          Clinical and basic science researchers in the Intramural Research Program at the National Institutes of Health were surveyed about their attitudes toward and experiences with sharing and reusing research data. Of 190 respondents to the survey, the 135 respondents who identified themselves as clinical or basic science researchers were included in this analysis. Odds ratio and Fisher’s exact tests were the primary methods to examine potential relationships between variables. Worst-case scenario sensitivity tests were conducted when necessary.

          Results and Discussion

          While most respondents considered data sharing and reuse important to their work, they generally rated their expertise as low. Sharing data directly with other researchers was common, but most respondents did not have experience with uploading data to a repository. A number of significant differences exist between the attitudes and practices of clinical and basic science researchers, including their motivations for sharing, their reasons for not sharing, and the amount of work required to prepare their data.

          Conclusions

          Even within the scope of biomedical research, addressing the unique concerns of diverse research communities is important to encouraging researchers to share and reuse data. Efforts at promoting data sharing and reuse should be aimed at solving not only technological problems, but also addressing researchers’ concerns about sharing their data. Given the varied practices of individual researchers and research communities, standardizing data practices like data citation and repository upload could make sharing and reuse easier.

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          Most cited references25

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          Evaluating re-identification risks with respect to the HIPAA privacy rule.

          Many healthcare organizations follow data protection policies that specify which patient identifiers must be suppressed to share "de-identified" records. Such policies, however, are often applied without knowledge of the risk of "re-identification". The goals of this work are: (1) to estimate re-identification risk for data sharing policies of the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule; and (2) to evaluate the risk of a specific re-identification attack using voter registration lists. We define several risk metrics: (1) expected number of re-identifications; (2) estimated proportion of a population in a group of size g or less, and (3) monetary cost per re-identification. For each US state, we estimate the risk posed to hypothetical datasets, protected by the HIPAA Safe Harbor and Limited Dataset policies by an attacker with full knowledge of patient identifiers and with limited knowledge in the form of voter registries. The percentage of a state's population estimated to be vulnerable to unique re-identification (ie, g=1) when protected via Safe Harbor and Limited Datasets ranges from 0.01% to 0.25% and 10% to 60%, respectively. In the voter attack, this number drops for many states, and for some states is 0%, due to the variable availability of voter registries in the real world. We also find that re-identification cost ranges from $0 to $17,000, further confirming risk variability. This work illustrates that blanket protection policies, such as Safe Harbor, leave different organizations vulnerable to re-identification at different rates. It provides justification for locally performed re-identification risk estimates prior to sharing data.
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            Megascience. 'Omics data sharing.

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              PRIDE Converter: making proteomics data-sharing easy.

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                24 June 2015
                2015
                : 10
                : 6
                : e0129506
                Affiliations
                [001]NIH Library, Division of Library Services, Office of Research Services, National Institutes of Health, Bethesda, Maryland, United States of America
                National Center for Toxicological Research, US Food and Drug Administration, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LMF DJJ. Performed the experiments: LMF. Analyzed the data: LMF YL DJJ JW BB. Wrote the paper: LMF YL DJJ JW BB.

                Article
                PONE-D-15-01701
                10.1371/journal.pone.0129506
                4481309
                26107811
                2c78f25a-1725-4b2f-9c8c-1843ff52b255

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication

                History
                : 13 January 2015
                : 8 May 2015
                Page count
                Figures: 2, Tables: 16, Pages: 17
                Funding
                The authors have no support or funding to report.
                Categories
                Research Article
                Custom metadata
                All data are available from Figshare at http://dx.doi.org/10.6084/m9.figshare.1288935.

                Uncategorized
                Uncategorized

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