Comparison of Mapping Techniques

نویسندگان

  • Fausto Giunchiglia
  • Marco Schorlemmer
  • Fiona McNeill
  • Alan Bundy
  • Maurizio Marchese
  • Mikalai Yatskevich
  • Ilya Zaihrayeu
  • Bo Hu
  • Vanessa Lopez
  • Marta Sabou
  • Joaquin Abian
  • Ronny Siebes
  • Spyros Kotoulas
  • Pavel Shvaiko
  • Bo Ho
  • Joaquı́n Abian
چکیده

Matching has been recognized as a plausible solution for the semantic heterogeneity problem in many traditional applications, such as schema integration, ontology integration, data warehouses, data integration, and so on. Recently, there have emerged a line of new applications characterized by their dynamics, such as peer-to-peer systems, agents, web-services. In this deliverable we extend the notion of ontology matching, as it has been understood in traditional applications, to dynamic ontology matching. In particular, we examine real-world scenarios and collect the requirements they pose towards a plausible solution. We consider five general matching directions which we believe can appropriately address those requirements. These are: (i) approximate and partial ontology matching, (ii) interactive ontology matching, (iii) continuous ”design-time” ontology matching, (iv) community-driven ontology matching and (v) multi-ontology matching. We give an overview of state of the art matching systems as well as their evaluation principles from the dynamic ontology matching perspective. Finally, the key open issues and challenges towards a plausible dynamic ontology matching solution are discussed, thereby providing a vision for future activities. OpenKnowledge is a 3 year long STReP project financed under the European Commission’s 6th Framework Programme. See, http://www.openk.org/ for details.

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تاریخ انتشار 2008