• DocumentCode
    168359
  • Title

    Research networks in data repositories

  • Author

    Costa, M.R. ; Jian Qin ; Jun Wang

  • Author_Institution
    Sch. of Inf. Studies, Syracuse Univ., Syracuse, NY, USA
  • fYear
    2014
  • fDate
    8-12 Sept. 2014
  • Firstpage
    403
  • Lastpage
    406
  • Abstract
    This paper reports our ongoing work investigating the structural features of scientific collaboration based on metadata collected from a scientific data repository (SDR). The background literature is reviewed in supporting our claim that metadata collected from SDRs offer a complimentary data source to traditional publication metadata collected from digital libraries. Methodological considerations are discussed in association with using metadata from SDRs, including author name disambiguation and data parsing. Initial findings show that the network has some unique macro-level structural features while also in agreement with existing networks theories. Challenges due to inconsistent metadata quality control procedures are also discussed in an attempt to reinforce claims that metadata should be designed to support both domain specific retrieval and evaluation and assessment needs.
  • Keywords
    data integration; digital libraries; meta data; SDR; complex network analysis; complimentary data source; digital libraries; metadata; metadata quality control procedures; network theories; publication metadata; scientific data repository; unique macrolevel structural features; Abstracts; Collaboration; Databases; Educational institutions; Scientific data repositories; complex network analysis; metadata; scientific collaboration; scientific collaboration networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Libraries (JCDL), 2014 IEEE/ACM Joint Conference on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1109/JCDL.2014.6970197
  • Filename
    6970197