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      If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology

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          Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center. We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies. CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities.

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          Sharing Detailed Research Data Is Associated with Increased Citation Rate

          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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            Challenges and opportunities of open data in ecology.

            Ecology is a synthetic discipline benefiting from open access to data from the earth, life, and social sciences. Technological challenges exist, however, due to the dispersed and heterogeneous nature of these data. Standardization of methods and development of robust metadata can increase data access but are not sufficient. Reproducibility of analyses is also important, and executable workflows are addressing this issue by capturing data provenance. Sociological challenges, including inadequate rewards for sharing data, must also be resolved. The establishment of well-curated, federated data repositories will provide a means to preserve data while promoting attribution and acknowledgement of its use.
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              Big data: How do your data grow?

              Ryan Lynch (2008)

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                23 July 2013
                : 8
                : 7
                : e67332
                [1]Department of Information Studies, Graduate School of Education and Information Studies, University of California Los Angeles, Los Angeles, California, United States of America
                Northwestern University, United States of America
                Author notes

                Competing Interests: The authors received money from Microsoft Technical Computing and External Research. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: JCW CLB. Performed the experiments: JCW CLB. Analyzed the data: JCW ER. Wrote the paper: JCW ER CLB.


                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.

                : 29 October 2012
                : 20 May 2013
                Page count
                Pages: 17
                Research reported here was supported in part by grants from the National Science Foundation (NSF): (1) The Center for Embedded Networked Sensing (CENS) is funded by NSF Cooperative Agreement number CCR-0120778, Deborah L. Estrin, UCLA, Principal Investigator; (2) Towards a Virtual Organization for Data Cyberinfrastructure, number OCI-0750529, C.L. Borgman, UCLA, PI; G. Bowker, Santa Clara University, Co-PI; Thomas Finholt, University of Michigan, Co-PI; (3) Monitoring, Modeling & Memory: Dynamics of Data and Knowledge in Scientific Cyberinfrastructures: number 0827322, P.N. Edwards, UM, PI; Co-PIs C.L. Borgman, UCLA; G. Bowker, SCU and Pittsburgh; T. Finholt, UM; S. Jackson, UM; D. Ribes, Georgetown; S.L. Star, SCU and Pittsburgh; and (4) The Data Conservancy, NSF Cooperative Agreement (DataNet) award OCI0830976, Sayeed Choudhury, PI, Johns Hopkins University. Microsoft Technical Computing and External Research provided gifts in support of this research program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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