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  • × classification_ss:"AK 39950"
  • × year_i:[2010 TO 2020}
  1. Borgman, C.L.: Big data, little data, no data : scholarship in the networked world (2015) 0.04
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    Abstract
    "Big Data" is on the covers of Science, Nature, the Economist, and Wired magazines, on the front pages of the Wall Street Journal and the New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data -- because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure -- an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation -- six "provocations" meant to inspire discussion about the uses of data in scholarship -- Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.
    Date
    14.10.2013 19:29:54
    LCSH
    Research / Data processing
    RSWK
    Forschung / Datenverarbeitung / Informationssystem / Wissenschaft / E-Science
    Subject
    Forschung / Datenverarbeitung / Informationssystem / Wissenschaft / E-Science
    Research / Data processing
  2. Herb, U.: Open Science in der Soziologie : eine interdisziplinäre Bestandsaufnahme zur offenen Wissenschaft und eine Untersuchung ihrer Verbreitung in der Soziologie (2015) 0.00
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    Abstract
    Die Arbeit basiert auf einer fachübergreifenden Bestandsaufnahme der Open-Science-Elemente 'Open Access zu Textpublikationen', 'Open Access zu Forschungsdaten', 'Open Access zu Forschungssoftware', 'Open Review' und 'Open Metrics', die allesamt typischerweise eher in den STM-Fächern (Science, Technology, Medicine) zu finden sind als in den Sozial- oder Geisteswissenschaften.