• DocumentCode
    3280878
  • Title

    Browsing Unbounded Social, Linked Data Instances with User Perspectives

  • Author

    Namgoong, Hyun ; Yang, Sungkwon ; Song, Mina ; Kim, Hong-Gee

  • Author_Institution
    Biomed. Eng. Lab., Seoul Nat. Univ., Seoul, South Korea
  • fYear
    2009
  • fDate
    20-22 July 2009
  • Firstpage
    352
  • Lastpage
    355
  • Abstract
    With the emerging uses of semantically enriched social data on the Web, linked data are expected to envision a next generation of the current web. As dasiaweb of datapsila, they are spread as pieces of data into the Web with links to related objects or concepts. Data instances distributed with URIs, those that enable identification and combination of data instances, can be consumed with shared data vocabularies. Easy and intuitive access to the data should be provided for data-centered uses of the Web. This paper introduces a linked data browser providing an intuitive view, especially helping casual userspsila understanding of data instances and their relationships. The browser also satisfies the requirement of a generic browser: handling unexpected domains of data across the links. By adapting userpsilas perspectives captured during browsing, the browser enables users to view any types of linked data instances with different views pertinent to their intentions and types of data.
  • Keywords
    Internet; online front-ends; social aspects of automation; social networking (online); URI; World Wide Web; casual users; data instance browsing; linked data browser; linked data instances; semantically enriched social data; shared data vocabularies; unbounded social instances; unexpected domain; user perspective; Biomedical engineering; Content management; Data mining; Data visualization; Joining processes; Next generation networking; Resource description framework; Semantic Web; Social network services; Vocabulary; data visualization; linked data; user perspective adaptation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in
  • Conference_Location
    Athens
  • Print_ISBN
    978-0-7695-3689-7
  • Type

    conf

  • DOI
    10.1109/ASONAM.2009.47
  • Filename
    5231835