• DocumentCode
    2351019
  • Title

    Case Study on Multi-classifications Based Scientific Data Management and Analysis System

  • Author

    Song, Jie ; Bao, Yubin ; Shi, Jingang ; Yu, Ge

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • Volume
    2
  • fYear
    2009
  • fDate
    11-14 Oct. 2009
  • Firstpage
    272
  • Lastpage
    277
  • Abstract
    The polymorphic, diversified, multi-sources and multi-use scientific data is quite different from the other data, there are many new challenges in building Scientific Data Management and Analysis System (SDMAS), especial one is that the multi-use data requires alternate classifications and mappings between them. Based on the oceanographic data, we present the solutions of multi-classifications problems. We first introduced the data and classificatory criterions of this case, then adopt the classification ontology to represent multi-classifications, use the metadata, query builder and data view mechanisms to support the dynamic cross-classification oriented query. We also prove the purposed solutions by applications and experiments. Theories and practices prove that the proposed solutions are contributed to build multi-classification based SDMAS.
  • Keywords
    data analysis; meta data; natural sciences computing; oceanography; pattern classification; query processing; Scientific Data Management and Analysis System; classification ontology; classificatory criterion; data view mechanism; dynamic cross-classification oriented query; metadata; multiclassifications problem; oceanographic data; query builder; Buildings; Conference management; Data analysis; Distributed databases; Engineering management; Information analysis; Information technology; Instruments; Multiaccess communication; Technology management; Multi-classifications; Scientific Data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology, 2009. CIT '09. Ninth IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-0-7695-3836-5
  • Type

    conf

  • DOI
    10.1109/CIT.2009.89
  • Filename
    5329083