Data sharing and duplication - Is there a problem?

Archives of Pediatrics and Adolescent Medicine (Impact Factor: 5.73). 10/2004; 158(9):931-2. DOI: 10.1001/archpedi.158.9.931
Source: PubMed
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    • "Increasing numbers of scholarly journals have been supporting this movement by adopting rules that encourage authors to make replication data sets available or that require them as a condition of publication. And scholars in a variety of other fields have encouraged the support of related agendas, including sociology (Freese 2007 [this issue]), economics (Anderson et al. 2005), medicine (Bachrach and King 2004), psychology (Johnson 2001), education (Schneider 2004), engineering (Whitbeck 2005), earth sciences (Board on Earth Sciences and Resources 2002), life sciences (Board on Life Sciences 2003), and others (Klump et al. 2006). Although many debates among scholars have occurred over the nature of replication requirements, and some opposition remains, the trend in most fields is strongly in favor of some version of these rules. "
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    ABSTRACT: We introduce a set of integrated developments in web application software, networking, data citation standards, and statistical methods designed to put some of the universe of data and data sharing practices on somewhat firmer ground. We have focused on social science data, but aspects of what we have developed may apply more widely. The idea is to facilitate the public distribution of persistent, authorized, and verifiable data, with powerful but easy-to-use technology, even when the data are confidential or proprietary. We intend to solve some of the sociological problems of data sharing via technological means, with the result intended to benefit both the scientific community and the sometimes apparently contradictory goals of individual researchers. Government Version of Record
    Sociological Methods &amp Research 11/2007; 36(2). DOI:10.1177/0049124107306660 · 1.52 Impact Factor
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    ABSTRACT: Data sharing provides many potential benefits, although the amount of actual data reused is unknown. Here we track the reuse of data from three data repositories (NCBI's Gene Expression Omnibus, PANGAEA, and TreeBASE) by searching for dataset accession number or unique identifier in Google Scholar and using ISI Web of Science to find articles that cited the data collection article. We found that data reuse and data attribution patterns vary across repositories. Data reuse appears to correlate with the number of citations to the data collection article. This preliminary investigation has demonstrated the feasibility of this method for tracking data reuse.
    Proceedings of the American Society for Information Science and Technology 01/2011; 48(1). DOI:10.1002/meet.2011.14504801337