Towards Ontology Matching for Intelligent Gadgets

  • Oszkar Ambrus
  • Knud Möller
  • Siegfried Handschuh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6275)


The FAST gadget development environment allows users to graphically compose intelligent, i.e., semantically annotated gadgets from predefined building blocks and deploy them on various mashup platforms, thus enabling the interconnection of different systems and services. In an environment where different parties use different ontologies to describe such building blocks, ontology matching is crucial. This paper discusses first steps in our effort to integrate ontology matching in an end-user-oriented environment such as FAST. We evaluate a number of tools and approaches for solving different levels of complexity in ontology matching and define the direction of integrating ontology matching into FAST.


ontology matching end-user mashups gadgets widgets 


  1. 1.
    Hoyer, V., Janner, T., Delchev, I., Lpez, J., Ortega, S., Fernndez, R., Möller, K., Rivera, I., Reyes, M., Fradinho, M.: The FAST platform: An open and semantically-enriched platform for designing multi-channel and enterprise-class gadgets. In: Baresi, L., Chi, C.-H., Suzuki, J. (eds.) ICSOC-ServiceWave 2009. LNCS, vol. 5900, pp. 316–330. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  2. 2.
    Hoyer, V., Stanoesvka-Slabeva, K., Janner, T., Schroth, C.: Enterprise mashups: Design principles towards the long tail of user needs. In: SCC 2008: Proceedings of the 2008 IEEE International Conference on Services Computing, pp. 601–602 (2008)Google Scholar
  3. 3.
    Gruber, T.R.: Towards Principles for the Design of Ontologies Used for Knowledge Sharing. In: Guarino, N., Poli, R. (eds.) Formal Ontology in Conceptual Analysis and Knowledge Representation. Kluwer Academic Publishers, The Netherlands (1993)Google Scholar
  4. 4.
    Shvaiko, P., Euzenat, J.: A survey of schema-based matching approaches. Journal on Data Semantics 4, 146–171 (2005)zbMATHGoogle Scholar
  5. 5.
    Euzenat, J.: An API for ontology alignment. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 698–712. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  6. 6.
    Scharffe, F., de Bruijn, J.: A language to specify mappings between ontologies. In: Proc. of the Internet Based Systems IEEE Conference, SITIS 2005 (2005)Google Scholar
  7. 7.
    de Bruijn, J., Lausen, H.: Web service modeling language (WSML). Member submission, W3C (June 2005)Google Scholar
  8. 8.
    Maedche, A., Motik, B., Silva, N., Volz, R.: Mafra — a mapping framework for distributed ontologies. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, p. 235. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  9. 9.
    Omelayenko, B.: RDFT: A mapping meta-ontology for business integration. In: Proceedings of the Workshop on Knowledge Transformation forthe Semantic Web (KTSW 2002), Lyon, France, pp. 76–83 (2002)Google Scholar
  10. 10.
    Hepp, M.: GoodRelations: An ontology for describing products and services offers on the web. In: Gangemi, A., Euzenat, J. (eds.) EKAW 2008. LNCS (LNAI), vol. 5268, pp. 332–347. Springer, Heidelberg (2008)Google Scholar
  11. 11.
    Fellbaum, C., et al.: WordNet: An electronic lexical database. MIT Press, Cambridge (1998)zbMATHGoogle Scholar
  12. 12.
    Olson, D., Delen, D.: Advanced data mining techniques. Springer, Heidelberg (2008)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Oszkar Ambrus
    • 1
  • Knud Möller
    • 1
  • Siegfried Handschuh
    • 1
  1. 1.Digital Enterprise Research Institute (DERI)National University of IrelandGalway (NUIG)Ireland

Personalised recommendations