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  • 标题:Archivist! Data Librarian! Asset Manager! Do the Differences Really Matter?
  • 本地全文:下载
  • 作者:Wendy Hagenmaier ; Dana M. Lamparello ; Karen S. Baker
  • 期刊名称:Bulletin of the American Society for Information Science
  • 出版年度:2015
  • 卷号:41
  • 期号:2
  • 出版社:American Society for Information Science and Technology
  • 摘要:

    Research data management librarian; digital asset manager; archivist/digital data specialist; born-digital processor; curation archivist; data curator – all of these positions have come online recently to address the explosive growth of digital data. What they all have in common – despite their varying titles – is digital data management. So why the variety of titles? Are we using different names for the same work? We developed this session at the Society of American Archivists 2014 Annual Meeting [ 1 ] as a series of breakout discussion groups around the themes of data creation, access and reuse to highlight areas in which data management roles overlap. The panelists represented four archetypal roles commonly encountered in the digital data world – archivist, embedded data manager, data librarian and data user – but were motivated by a desire to break down barriers extant among such positions and to explore the diversity of data and information needs in practice. Our session was intended as a first step in collectively developing a common conceptual understanding of semantics and roles to bridge disparate professional communities, including the archives community, research data management community, digital curation community and digital humanities community, among others. This column is a brief overview of the session, but we encourage you to join the continuing discussion by commenting here: goo.gl/yCRHqG Data Creation Digital data creation is a complex phenomenon encountered by the archetypes in differing circumstances. Researchers, for instance, create data in the field and laboratory. Yet dataset creation may also be recognized as occurring at the moment of repository submission. Or given the reproducibility of digital data, copies of the same dataset may reside in several different repositories where each views ingestion as a moment of creation. And finally, data creation may be identified during assembly of a new collection from pre-existing data.

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