Advertisement

A Timing Analysis Model for Ontology Evolutions Based on Distributed Environments

  • Yinglong Ma
  • Beihong Jin
  • Yuancheng Li
  • Kehe Wu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4426)

Abstract

In order to reuse and assess ontologies, it is critical for ontology engineers to represent and manage ontology versioning and evolutions. In this paper, we propose a timing analysis model for ontology evolution management with more expressive time constraints in a distributed environment. In the model, a timing change operation sequence is called a timing evolution behavior that must satisfy all of the time constraints in a distributed environment. Using this timing analysis model, we can detect whether ontology evolutions are timing consistent in the distributed environment. Given a timing change operation sequence, we also can detect whether it is a timing evolution behavior of the distributed environment. All of these detections can be reduced to detecting whether the group of inequations has solutions. This enables us to better manage dynamic versioning and evolutions of distributed ontologies. We also developed a prototype system called TEAM that can perform our timing analysis task of distributed ontology evolutions.

Keywords

Evolution Behavior Ontology Evolution Single Context Ontology Engineer Ontology Change 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Neches, R., et al.: Enabling Technology for Knowledge Sharing. AI Magazine 12(3), 36–56 (1991)Google Scholar
  2. 2.
    Hendler, J.: Agents and the Semantic Web. IEEE Intelligent Systems 16, 30–37 (2001)CrossRefGoogle Scholar
  3. 3.
    Klein, M., et al.: Ontology Versioning and Change Detection on the Web. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 197–212. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  4. 4.
    Noy, N.F., Musen, M.A.: Ontology Versioning in an Ontology Management Framework. IEEE Intelligent System 19(4), 6–13 (2004)CrossRefGoogle Scholar
  5. 5.
    Noy, N., et al.: The Prompt Suite: Interactive Tools for Ontology Mergin and Mapping. International Journal of Human-Computer Studies 59(6), 983–1024 (2003)CrossRefGoogle Scholar
  6. 6.
    Ehrig, M., Staab, S.: QOM - Quick Ontology Mapping. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 683–696. Springer, Heidelberg (2004)Google Scholar
  7. 7.
    Compatangelo, E., Vasconcelos, W., Scharlau, B.: Managing Ontology Versions with A Distributed Blackboard Architecture. In: Proceedings of the 24th Int Conf. of the British Computer Societys Specialist Group on Artificial Intelligence (AI2004), Springer, Heidelberg (2004)Google Scholar
  8. 8.
    Huang, Z., Stuckenschmidt, H.: Reasoning with Multiversion Ontologies – A Temporal Logic Approach. In: Gil, Y., et al. (eds.) ISWC 2005. LNCS, vol. 3729, Springer, Heidelberg (2005)CrossRefGoogle Scholar
  9. 9.
    Clarke, E.M., et al.: Model Checking. MIT Press, Cambridge (1999)Google Scholar
  10. 10.
    LINDO System INC. LINDO System API 4.1 (2006), http://lindo.com/products/api/dllm.html

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Yinglong Ma
    • 1
    • 2
  • Beihong Jin
    • 2
  • Yuancheng Li
    • 1
  • Kehe Wu
    • 1
  1. 1.Computer Sciences and Technology Department, North China Electric Power University, Beijing 102206P.R. China
  2. 2.Technology Center of Software Engineering, Institute of Software, Chinese Academy of Sciences, P.O.Box 8718, Beijing 100080P.R. China

Personalised recommendations