Transformation from OWL Description to Resource Space Model

  • Hai Zhuge
  • Peng Shi
  • Yunpeng Xing
  • Chao He
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4185)


Semantics shows diversity in real world, document world, mental abstraction world and machine world. Transformation between semantics pursues the uniformity in the diversity. The Resource Space Model (RSM) is a semantic data model for organizing resources based on the classification semantics that human often use in understanding the real world. The design of a resource space relies on knowledge about domain and the RSM. Automatically creating resource space can relieve such reliance in RSM applications. This paper proposes an approach to automatically transform Web Ontology Language description into resource space. The normal forms of the generated resource space are investigated to ensure its normalization characteristic. The Dunhuang culture resource space is used to illustrate the approach.


Unify Modeling Language Classification Semantic Resource Space Inheritance Hierarchy Concrete Class 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Assem, M., Menken, M.R., Schreiber, G., Wielemaker, J., Wielinga, B.J.: A Method for Converting Thesauri to RDF/OWL. In: International Semantic Web Conference, Hiroshima, Japan, pp. 17–31 (2004)Google Scholar
  2. 2.
    Batini, C., Ceri, S., Navathe, S.B.: Conceptual Database Design: an Entity-Relationship Approach. Benjamin and Cummings Publ. Co., Menlo Park (1992)zbMATHGoogle Scholar
  3. 3.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284(5), 34–43 (2001)CrossRefGoogle Scholar
  4. 4.
    Chen, P.P.: The Entity-Relationship Model, Towards a Unified View of Data. ACMTransactions on Database Systems 1(1), 9–36 (1976)CrossRefGoogle Scholar
  5. 5.
    Embley, D.W.: Object Database Development Concepts and Principles. Addison-Wesley, Reading (1997)zbMATHGoogle Scholar
  6. 6.
    Gaševic, D., Djuric, D., Devedžic, V., Damjanovic, V.: Converting UML to OWL Ontologies. In: Proceedings of the 13th International World Wide Web Conference, NY, USA, pp. 488–489 (2004)Google Scholar
  7. 7.
    Grønmo, R., Jaeger, M.C., Hoff, H.: Transformations between UML and OWL-S. In: Hartman, A., Kreische, D. (eds.) ECMDA-FA 2005. LNCS, vol. 3748, pp. 269–283. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  8. 8.
    Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5(2), 199–220 (1993)CrossRefGoogle Scholar
  9. 9.
    Hepp, M.: A Methodology for Deriving OWL Ontologies from Products and Services Categorization Standards. In: Proceedings of the 13th European Conference on Information Systems (ECIS 2005), Regensburg, Germany, pp. 1–12 (2005)Google Scholar
  10. 10.
    Kaljurand, K.: From ACE to OWL and from OWL to ACE. The third REWERSE annual meeting, Munich (March 2006)Google Scholar
  11. 11.
    Marca, D., McGowan, C.: SADT: Structured Analysis and Design Techniques. McGraw- Hill, New York (1987)Google Scholar
  12. 12.
    Motik, B., Vrandecic, D., Hitzler, P., Sure, Y., Studer, R.: dlpconvert - Converting OWL DLP Statements to Logic Programs. In: System Demo at the 2nd European Semantic Web Conference, Iraklion, Greece (May 2005)Google Scholar
  13. 13.
    Ng, P.A.: Further Analysis of the Entity-Relationship Approach to Database Design. IEEE Transaction on Software Engineer 7(1), 85–99 (1981)CrossRefGoogle Scholar
  14. 14.
    Neches, R., Fikes, R.E., Gruber, T.R., Patil, R., Senator, T., Swartout, W.: Enabling Technology for Knowledge Sharing. AI Magazine 12(3), 36–56 (1991)Google Scholar
  15. 15.
    Teorey, T., Yang, D., Fry, J.: A Logical Design Methodology for Relational Databases Using the Extended Entity-Relationship Model. ACM Computing Surveys 18(2) (June, 1986)Google Scholar
  16. 16.
    Zhuge, H.: Resource Space Grid: Model, Method and Platform. Concurrency and Computation: Practice and Experience 16(14), 1385–1413 (2004)CrossRefGoogle Scholar
  17. 17.
    Zhuge, H.: The Knowledge Grid. World Scientific, Singapore (2004)Google Scholar
  18. 18.
    Zhuge, H.: Resource Space Model, Its Design Method and Applications. Journal of Systems and Software 72(1), 71–81 (2004)CrossRefGoogle Scholar
  19. 19.
    Zhuge, H., Xing, Y.: Integrity Theory for Resource Space Model and Its Application, Keynote. In: Fan, W., Wu, Z., Yang, J. (eds.) WAIM 2005. LNCS, vol. 3739, pp. 8–24. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  20. 20.
    Zhuge, H., Yao, E., Xing, Y., Liu, J.: Extended Normal Form Theory of Resource Space Model. Future Generation Computer Systems 21(1), 189–198 (2005)CrossRefGoogle Scholar
  21. 21.
    Zhuge, H.: The Open and Autonomous Interconnection Semantics. In: Keynote at 8th International Conference on Electronic Commerce, August 14-16, Fredericton, New Brunswick, Canada (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hai Zhuge
    • 1
  • Peng Shi
    • 1
  • Yunpeng Xing
    • 1
  • Chao He
    • 1
  1. 1.China Knowledge Grid Research Group, Key Laboratory of Intelligent Information Processing, Institute of Computing TechnologyChinese Academy of SciencesBeijingChina

Personalised recommendations