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  • 标题:Using Data Management Plans to Explore Variability in Research Data Management Practices Across Domains
  • 本地全文:下载
  • 作者:Susan Wells Parham ; Jake Carlson ; Patricia Hswe
  • 期刊名称:International Journal of Digital Curation
  • 印刷版ISSN:1746-8256
  • 出版年度:2016
  • 卷号:11
  • 期号:1
  • 页码:53-67
  • DOI:10.2218/ijdc.v11i1.423
  • 语种:English
  • 出版社:University of Edinburgh
  • 摘要:This paper describes an investigation into how researchers in different fields are interpreting and responding to the U.S. National Science Foundation’s data management plan (DMP) requirement. As documents written by the researchers themselves, DMPs can provide insight into researchers’ understanding of the potential value of their data to others; the environment in which their data are developed and prepared; and their willingness and ability to ensure the data are available to others now and in the long-term. With support from the Institute of Museum and Library Services, the authors conducted a content analysis of DMPs generated at their respective institutions using a shared rubric. By developing and testing a rubric designed to understand and evaluate the content of DMPs, the authors intend to develop a more complete understanding, at a larger scale, of how researchers plan for managing, sharing, and archiving their data. Â
  • 其他摘要:This paper describes an investigation into how researchers in different fields are interpreting and responding to the U.S. National Science Foundation’s data management plan (DMP) requirement. As documents written by the researchers themselves, DMPs can provide insight into researchers’ understanding of the potential value of their data to others; the environment in which their data are developed and prepared; and their willingness and ability to ensure the data are available to others now and in the long-term. With support from the Institute of Museum and Library Services, the authors conducted a content analysis of DMPs generated at their respective institutions using a shared rubric. By developing and testing a rubric designed to understand and evaluate the content of DMPs, the authors intend to develop a more complete understanding, at a larger scale, of how researchers plan for managing, sharing, and archiving their data.
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