Reconciling Heterogeneous Knowledge with Ontology Matching
In open, dynamic and distributed systems, it is unrealistic to assume that autonomous agents or peers are committed to a common way of expressing their knowledge, in terms of one or more ontologies modelling the domain of interest. Thus, before any kind o
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Reconciling Heterogeneous Knowledge with Ontology Matching Cássia Trojahn and George Vouros
6.1 Introduction In open, dynamic and distributed systems, it is unrealistic to assume that autonomous agents or peers are committed to a common way of expressing their knowledge, in terms of one or more ontologies modeling the domain of interest. Thus, before any kind of communication or cooperation, agents must reach an agreement on the meaning of the terms they use for structuring information, conceptualizing the world, or representing distinct entities. Reaching semantic agreements between ontologies is necessary in (a) distributed settings where autonomous agents do not share common vocabularies and conceptualizations, in (b) peer data management systems where peers are heterogeneous to the data schema they use, and also, as a worth-mentioning refined case of (a), (c) for different ontology alignment and instance matching methods to synthesize their results. We may distinguish two generic problem cases where reaching semantic agreements (i.e., agreements that preserve the semantics of the representations) between the mapping decisions of heterogeneous agents is of particular value: 1. Two or more agents have the same ontologies and need to produce mappings to the ontology elements of another entity: In this case, entities need to reach agreements concerning the mappings of the ontology elements they share to the ontology elements of the third entity.
C. Trojahn () INRIA & LIG, Grenoble, France e-mail: [email protected] G. Vouros Department of Digital Systems, University of Piraeus, Piraeus, Greece e-mail: [email protected] S. Ossowski (ed.), Agreement Technologies, Law, Governance and Technology Series 8, DOI 10.1007/978-94-007-5583-3__6, © Springer Science+Business Media Dordrecht 2013
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2. There is a network of entities, whereby each entity is connected to its “known neighbours”. Entities do not necessarily share the same ontology. In this setting each entity need to produce mappings between its own ontology and the ontology of each of its neighbours. Entities need to reach agreements on their mappings so that there is a consistent set of mappings in the network as a whole. Over the years several approaches have been proposed for achieving semantic agreement based on ontology matching in a distributed setting: argumentation-based models, constraint satisfaction methods and probabilistic models. The aim of this chapter is to present a brief overview of the state-of-the-art on these approaches and discuss the main open issues and challenges for future research. We firstly introduce the ontology matching process for semantic agreements (Sect. 6.2) and the notion of argumentation frameworks (Sect. 6.3), and then we present scenarios applying such frameworks (Sect. 6.3.4). Next, we specify the problem of synthesizing different matching methods as a constraint optimization problem and show the benefits of this approach (Sect. 6.4) and we present an approach for peers organized in ar
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