SOR: a practical system for ontology storage, reasoning and search

  • Authors:

  • Jing Lu;Li Ma;Lei Zhang;Jean-Sébastien Brunner;Chen Wang;Yue Pan;Yong Yu

  • Affiliations:

  • IBM China Research Laboratory, ShangDi, Beijing, China and Shanghai JiaoTong University, Shanghai, China;IBM China Research Laboratory, ShangDi, Beijing, China;IBM China Research Laboratory, ShangDi, Beijing, China;IBM China Research Laboratory, ShangDi, Beijing, China;IBM China Research Laboratory, ShangDi, Beijing, China;IBM China Research Laboratory, ShangDi, Beijing, China;Shanghai JiaoTong University, Shanghai, China

  • Venue:
  • VLDB '07 Proceedings of the 33rd international conference on Very large data bases
  • Year:
  • 2007

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Abstract

Ontology, an explicit specification of shared conceptualization, has been increasingly used to define formal data semantics and improve data reusability and interoperability in enterprise information systems. In this paper, we present and demonstrate SOR (Scalable Ontology Repository), a practical system for ontology storage, reasoning, and search. SOR uses Relational DBMS to store ontologies, performs inference over them, and supports SPARQL language for query. Furthermore, a faceted search with relationship navigation is designed and implemented for ontology search. This demonstration shows how to efficiently solve three key problems in practical ontology management in RDBMS, namely storage, reasoning, and search. Moreover, we show how the SOR system is used for semantic master data management.