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Refereed Papers

Track: Semantic Web

Paper Title:
Explorations in the Use of Semantic Web Technologies for Product Information Management

Authors:

  • Jean-Sebastien Brunner (IBM China Research Laboratory)
  • Li Ma (IBM China Research Laboratory)
  • Chen Wang (IBM China Research Laboratory)
  • Lei Zhang (IBM China Research Laboratory)
  • Daniel C. Wolfson (IBM Software Group)
  • Yue Pan (IBM China Research Laboratory)
  • Kavitha Srinivas (IBM T.J. Watson Research Center)

Abstract:
Master data refers to core business entities a company uses repeatedly across many business processes and systems (such as lists or hierarchies of customers, suppliers, accounts, products, or organizational units). Product information is the most important kind of master data and product information management (PIM) is becoming critical for modern enterprises because it provides a rich business context for various applications. Existing PIM systems are less flexible and scalable for on-demand business, as well as too weak to completely capture and use the semantics of master data. This paper explores how to use semantic web technologies to enhance a collaborative PIM system by simplifying modeling and representation while preserving enough dynamic flexibility. Furthermore, we build a semantic PIM system using one of the state-of-art ontology repositories and summarize the challenges we encountered based on our experimental results, especially on performance and scalability. We believe that our study and experiences are valuable for both semantic web community and master data management community.

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