RStar: an RDF storage and query system for enterprise resource management

  • Authors:

  • Li Ma;Zhong Su;Yue Pan;Li Zhang;Tao Liu

  • Affiliations:

  • IBM China Research Laboratory, ShangDi, Beijing, P.R. China;IBM China Research Laboratory, ShangDi, Beijing, P.R. China;IBM China Research Laboratory, ShangDi, Beijing, P.R. China;IBM China Research Laboratory, ShangDi, Beijing, P.R. China;IBM China Research Laboratory, ShangDi, Beijing, P.R. China

  • Venue:
  • Proceedings of the thirteenth ACM international conference on Information and knowledge management
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

Modern corporations operate in an extremely complex environment and strongly depend on all kinds of information resources across the enterprise. Unfortunately, with the growth of an enterprise, its information resources are not only heterogeneous but also distributed in physically different systems and databases. How to effectively exploit information across the enterprise is becoming a critical but hard problem. In recent years, metadata which is the detailed description of the data is used to efficiently exploit information resources in the web. The World Wide Web Consortium (W3C) recommends the resource description framework (RDF) as a standard for the definition and use of metadata descriptions of resources in the web. In this paper, we present an RDF storage and query system called RStar for enterprise resource management. RStar uses a relational database as the persistent data store and defines RStar Query Language (RSQL) for resource retrieval. Currently, most of existing RDF storage and query systems are evaluated on small data sets and no detailed performance analysis is given for such systems. Therefore, we conduct extensive experiments on a large scale data set to investigate the performance problem in RDF storage. Such analysis will be helpful for designing RDF storage and query systems as well as for understanding not well-solved issues in RDF based enterprise resource management. In addition, experiences and lessons learned in our implementation are presented for further research and development.