Ontology Integration and Merging
[edit] Contributors:
José Ángel Ramos and Boris Villazón Universidad Politécnica de Madrid Please add your CV in the list of contributors
[edit] Introduction
When the use of ontologies began to extend and the number of ontologies went up considerably, it was natural that the need to integrate ontologies also arose. The first approach to integrate ontologies was to merge them and, thus, to obtain a single ontology which would have/include all the knowledge that the merged ontologies had. The first ontology integration approaches were part of the ontology development, and they followed any methodology which would permit obtaining new ontologies [Uschold and King, 1995; Gruninger, 1996; Fernández-López et al., 1997] or merging of existing ontologies [Swartout et al., 1997].
Beyond ontology development, we can find many works on ontology integration, being the most important the following: ONIONS [Steve et al., 1997; Gangemi et al., 1999], PROMPT [Noy and Musen, 2000] (at first called SMART [Noy and Musen, 1999]), OBSERVER [Mena et al., 2000], Chimaera [McGuiness et al., 2000], OntoMorph [Chalupsky, 2000], FCA-Merge [Stumme and Maedche, 2001], MAFRA [Maedche et al., 2002], [Fernández-Breis and Martínez-Béjar, 2002], OntoMerge [Dou et al., 2002], WI-ONTO [Fernández-Breis et al., 2002] and as generic jobs like reference: [Pinto et al., 1999], [Calvanese et al., 2001] or [Noy, 2004].
In the literature we can find many definitions of ontology integration ([McGuiness et al., 2000; Pinto and Martins, 2001] as example) but we would like to point out the definition and partitions given by [Sowa, 2000]: “The process of finding commonalities between two different ontologies A and B and deriving a new ontology C that facilitates interoperability between computer systems that are base on the A and B ontologies. The new ontology C may replace A or B, or it may be used only as an intermediary between a system based on A and system based on B. Depending on the amount of change necessary to derive C from A and B, different levels of integration can be distinguished:”
These levels are:
Ontology Alignment: “Is the weakest form of integration: it requires minimal change, but it can only support limited kinds of interoperability. It is useful for classification and information retrieval, but it does not support deep inferences and computations.”
Ontology Partial Compatibility: “Requires more changes in order to support more extensive interoperability, even though there may be some concepts or relations in one system or the other that could create obstacles to full interoperability.”
And Ontology Unification or Total Compatibility: “May require changes or major reorganizations of A and B, but it can result in the most complete interoperability: everything that can be done with one can be done in a exactly equivalent way with the other.”
This last level is usually called Ontology Merge.
In the literature, and within the field of ontology integration we can observe that the concept of integration is unavoidably related to the idea of mapping and, therefore, of alignment. Although the term “mapping” is used in many areas, its definition has not been consensuated yet; therefore, it seems quite reasonable to think of mapping as the relation between two ontology components. Currently, most of the works carried out in this field are specifically on mappings and its lifecycle (discovery, composition, explotation) [Kalfoglou and Schorlemmer, 2005], and most particularly on the direct correspondence (equality) between same category components. However, the semantics of the mapping relation can be extended to express overlapping, subsumption, transformation, etc. [Noy and Stuckenschmidt, 2005]
Nowadays, there are quite a few methods to discover mappings [Bouquet et al., 2004] [Euzenat et al., 2006] and systems that integrate and manage such mappings. [Noy and Stuckenschmidt, 2005].
[edit] Bibliography
Bouquet P (coordinator), Euzenat J, Franconi E, Serafini L, Stamou G, Tessaris S (2004) D2.2.1 Specification of a common framework for characterizing alignment Knowledge Web (FP6-507482). http://www.knowledgeweb.net/
Calvanese D, De Giacomo G, Lenzerini M (2001) A framework for ontology integration. In Staab and Studer editors, Handbook on Ontologies, Springer, pp 321-342.
Chalupsky H (2000) OntoMorph: a translation system for symbolic knowledge. In: Cohn AG, Giunchiglia F, Selman B (eds) 7th International Conference on Knowledge Representation and Reasoning (KR’00). Breckenridge, Colorado. Morgan Kaufmann Publishers, San Francisco, California, pp 471–482
Dou D, McDermott D, Qi P (2002) Ontology translation by ontology merging and automated reasoning. In Proceedings of the EKAW Workshop on Ontologies for Multi-Agent Systems, Sigüenza, Spain.
Euzenat J, Mochol M, Shvaiko P, Stucknschmidt H, Svab O, Svatek V, van Hage WR, Yatskevich (2006) Results of the Ontology Alignment Evaluation Initiative 2006. Ontology Matching workshop at International Semantic Web Conference 2006. Athens, GA, USA on November 5, 2006.
Fernández-Breis JT, Martínez-Béjar R (2002) A cooperative framework to integrate ontologies. International Journal of Human-Computer Studies 56 (6), pp 665-720
Fernández-Breis JT, Menárguez M, Valencia R, Vivancos PJ (2005) WI-ONTO: A web tool for the automatic integration of ontologies. CAEPIA’2005. Vol. I, pp 253-262
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Gruninger, M. (1996), Designing and Evaluating Generic Ontologies, in ‘ECAI96’s workshop on Ontological Engineering’.
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Noy NF, Musen MA (2000) PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000). Austin, Texas
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Pinto HS, Martins JP. A methodology for ontology integration. In Proceedings of the International Conference on Knowledge Capture K-CAP2001, pages 131-138. ACM Press, 2001.
Sowa JF. Knowledge Representation: Logical, Philosophical and Computational Foundations. Brooks/Cole, 2000.
Steve G, Gangemi A, Pisanelli DM (1997) Integrating Medical Terminologies with ONIONS Methodology. In: Kangassalo H, Charrel JP (eds) Information Modeling and Knowledge Bases VIII. IOS Press, Amsterdam, The Netherlands. http://ontology.ip.rm.cnr.it/Papers/onions97.pdf
Stumme G, Maedche A (2001) FCA-Merge: Bottom-Up Merging of Ontologies IJCAI 2001 – Proceedings of the 17th International Joint Conference on Artificial Intelligent. Seattle, USA
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