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      Towards a Data Sharing Culture: Recommendations for Leadership from Academic Health Centers

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      Author(s): , , , * , on behalf of the caBIG Data Sharing and Intellectual Capital Workspace
      Publication date (Electronic):
      Journal: PLoS Medicine
      Publisher: Public Library of Science

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          Abstract

          Rebecca Crowley and colleagues propose that academic health centers can and should lead the transition towards a culture of biomedical data sharing.

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          Sharing Detailed Research Data Is Associated with Increased Citation Rate

          Heather A. Piwowar, Roger S. Day, Douglas Fridsma (2007)
          Background Sharing research data provides benefit to the general scientific community, but the benefit is less obvious for the investigator who makes his or her data available. Principal Findings We examined the citation history of 85 cancer microarray clinical trial publications with respect to the availability of their data. The 48% of trials with publicly available microarray data received 85% of the aggregate citations. Publicly available data was significantly (p = 0.006) associated with a 69% increase in citations, independently of journal impact factor, date of publication, and author country of origin using linear regression. Significance This correlation between publicly available data and increased literature impact may further motivate investigators to share their detailed research data.
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            Advancing translational research with the Semantic Web

            Alan Ruttenberg, Tim Clark, William Bug … (2007)
            Background A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. Results We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. Conclusion Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.
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              Whose data set is it anyway? Sharing raw data from randomized trials

              Andrew Vickers (2006)
              Background Sharing of raw research data is common in many areas of medical research, genomics being perhaps the most well-known example. In the clinical trial community investigators routinely refuse to share raw data from a randomized trial without giving a reason. Discussion Data sharing benefits numerous research-related activities: reproducing analyses; testing secondary hypotheses; developing and evaluating novel statistical methods; teaching; aiding design of future trials; meta-analysis; and, possibly, preventing error, fraud and selective reporting. Clinical trialists, however, sometimes appear overly concerned with being scooped and with misrepresentation of their work. Both possibilities can be avoided with simple measures such as inclusion of the original trialists as co-authors on any publication resulting from data sharing. Moreover, if we treat any data set as belonging to the patients who comprise it, rather than the investigators, such concerns fall away. Conclusion Technological developments, particularly the Internet, have made data sharing generally a trivial logistical problem. Data sharing should come to be seen as an inherent part of conducting a randomized trial, similar to the way in which we consider ethical review and publication of study results. Journals and funding bodies should insist that trialists make raw data available, for example, by publishing data on the Web. If the clinical trial community continues to fail with respect to data sharing, we will only strengthen the public perception that we do clinical trials to benefit ourselves, not our patients.
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                Author and article information

                Journal
                Journal ID (nlm-ta): PLoS Med
                Journal ID (publisher-id): pmed
                Journal ID (publisher-id): plme
                Journal ID (pmc): plosmed
                Title: PLoS Medicine
                Publisher: Public Library of Science (San Francisco, USA )
                ISSN (Print): 1549-1277
                ISSN (Electronic): 1549-1676
                Publication date (Print): September 2008
                Publication date (Electronic): 2 September 2008
                Volume: 5
                Issue: 9
                Electronic Location Identifier: e183
                Author notes
                * To whom correspondence should be addressed. E-mail: crowleyrs@ 123456upmc.edu
                Article
                Publisher ID: 08-PLME-PF-0748R2
                DOI: 10.1371/journal.pmed.0050183
                PMC ID: 2528049
                PubMed ID: 18767901
                SO-VID: 5e376d42-69f2-4402-bbda-331d32561eab
                Copyright © Copyright: © 2008 Piwowar et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                Page count
                Pages: 5
                Categories
                Subject: Policy Forum
                Subject: Biotechnology
                Subject: Non-Clinical Medicine
                Subject: Science Policy
                Subject: Medical Informatics
                Subject: Academic Medicine
                Subject: Health Policy
                Subject: Research Methods
                Subject: Research Design
                Custom metadata
                citation Piwowar HA, Becich MJ, Bilofsky H, Crowley RS, caBIG Data Sharing and Intellectual Capital Workspace (2008) Towards a data sharing culture: Recommendations for leadership from academic health centers. PLoS Med 5(9): e183. doi: 10.1371/journal.pmed.0050183

                ScienceOpen disciplines: Medicine
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                ScienceOpen disciplines: Medicine

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