2003 OntologyMappingStateofTheArt

From GM-RKB
Jump to: navigation, search

Subject Headings: Ontology Mapping Task, Ontology Mapping Algorithm, Ontology Mapping System.

Notes

Cited By

2006

Quotes

Abstract

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mappings has been the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping.

1. Introduction

Nowadays, the interested practitioner in ontology mapping, is often faced with a knotty problem: there is an enormous amount of diverse work originating from different communities who claim some sort of relevance to ontology mapping. For example, terms and works encountered in the literature which claimed to be relevant include: alignment, merging, articulation, fusion, integration, morphism, and so on. Given this diversity, it is difficult to identify the problem areas and comprehend solutions provided. Part of the problem is the lack of a comprehensive survey, a standard terminology, hidden assumptions or undisclosed technical details, and the dearth of evaluation metrics.

This article aims to fill-in some of these gaps, primarily the first one: lack of a comprehensive survey. We scrutinised the literature and critically reviewed works originating from a variety of fields to provide a comprehensive overview of ontology mapping work to date. We also worked on the theoretical grounds for defining ontology mapping, which could act as the glue for better understanding similarities and pinpointing differences in the works reported.

The overall goal of this paper is not only to give readers a comprehensive overview of the ontology mapping works to date, but also to provide necessary insights for the practical understanding of the issues involved. As such, we have been critiquing while reporting these works, and not just been descriptive. At the same time though, we objectively review the works with emphasis given on a practitioner’s interests, and try to provide answers to the following questions:

  • What are the lessons learnt from this work?
  • How easily can this work be replicated in similar domains?

2.a Defining ontology mapping

We shall adopt an algebraic approach and present ontologies as logical theories. An ontology is then a pair O = (S,A), where [math]S[/math] is the (ontological) signature describing the vocabulary — and [math]A[/math] is a set of (ontological) axioms — specifying the intended interpretation of the vocabulary in some domain of discourse. Typically, an ontological signature will be modelled by some mathematical structure. For instance, it could consist of a hierarchy of concept or class symbols modelled as a partial ordered set (poset), together with a set of relations symbols whose arguments are defined over the concepts of the concept hierarchy. The relations themselves might also be structured into a poset. For the purposes of this survey we shall not commit to any particular definition of ontological signature; we refer to the definitions of ‘ontology’, ‘core ontology’, or ‘ontology signature’ in (Kalfoglou and Schorlemmer 2002; Stumme and Maedche 2001; Bench-Capon and Malcolm 1999), respectively, for some examples of what we consider here an ontological signature. In addition to the signature specification, ontological axioms are usually restricted to a particular sort or class of axioms, depending on the kind of ontology.

Ontological signature morphisms. We understand ontology mapping as the task of relating the vocabulary of two ontologies that share the same domain of discourse in such a way that the mathematical structure of ontological signatures and their intended interpretations, as specified by the ontological axioms, are respected. Structure-preserving mappings between mathematical structures are called morphisms; for instance, a function f between two posets that preserves the partial order (a b implies f(a) f(b)) is a morphism of posets. Hence we shall characterise ontology mappings as morphisms of ontological signatures as follows.

A total ontology mapping from O1 = (S1,A1) to O2 = (S2,A2) is a morphism f : S1 → S2 of ontological signatures, such that, A2 |= f(A1), i.e., all interpretations that satisfy O2’s axioms also satisfy O1’s translated axioms. This makes an ontology mapping a theory morphism as it is usually defined in the field of algebraic specification (see, for instance, (Meseguer 1989)).

In order to accommodate a weaker notion of ontology mapping we will say that there is a partial ontology mapping form O1 = (S1,A1) to O2 = (S2,A2) if there exists a sub-ontology O 1 = (S 1, A 1) (S 1 ⊆ S1 and A 1 ⊆ A1) such that there is a total mapping from O 1 to O2.

Populated ontologies. Central to several approaches to ontology mapping is the concept of a populated ontology. In this case, classes of an ontological signature come equipped with their respective instances. A populated ontology can be characterised by augmenting the signature with a classification relation that defines the classification of instances to the concept symbols in the signature. This brings forth issues about the correctness of populated ontologies, namely if the classification of instances respects the structure of the ontological signature. See (Kalfoglou and Schorlemmer 2002) for a use of populated ontologies in the definition of ontology mapping.

Taking into account the population of ontologies when establishing the mapping between ontologies may be useful for relating concepts according to the meaning and use that these concepts are given by particular communities. This idea is theoretically described in (Kent 2000) and (Schorlemmer 2002), for instance, and is fundamental to the information-flow based approaches described in Section 3.f.

Ontology morphisms. So far, we have defined ontology mapping only in terms of morphisms of ontological signatures, i.e., by determining which concept and relation symbols of one ontology are mapped to concept and relation symbols of the other. A more ambitious and practically necessary approach would be to take into account how particular ontological axioms are mapped as well. Formally, this would require ontology mappings to be defined in terms of morphisms of ontologies, i.e., signature + axioms, instead of morphisms of signatures only.

Most works on ontology mapping reported here adopt the more restrictive view of ontology mapping as signature morphism. Nevertheless, some of them consider the alignment of logical sentences, and not of signature symbols only (Calvanese et al. 2001b; Madhavan et al. 2002). Thus, we will use the term ‘ontology mapping’ for mappings as ontological signature morphisms as well as mappings as ontology morphisms.

Ontology alignment, articulation and merging. Ontology mapping only constitutes a fragment of a more ambitious task concerning the alignment, articulation and merging of ontologies. Here we want to clarify our understanding of these concepts within the above theoretical picture. An ontology mapping is a morphism, which usually will consist of a collection of functions assigning the symbols used in one vocabulary to the symbols of the other. But two ontologies may be related in a more general fashion, namely by means of relations instead of functions. Hence, we will call ontology alignment the task of establishing a collection of binary relations between the vocabularies of two ontologies. Since a binary relation can itself be decomposed into a pair of total functions from a common intermediate source, we may describe the alignment of two ontologies O1 and O2 by means of a pair of ontology mappings from an intermediate source ontology O0 (see Figure 1). We shall call the intermediate ontology O0, together with its mappings, the articulation of two ontologies. For an example of ontology articulation see (Maedche and Staab 2000; Madhavan et al. 2002; Compatangelo and Meisel 2002).

Fig. 1. Diagrammatic views of articulation and merging of two ontologies.

  • Articulation: O1 ⇒ O2; O1 ⇒ O3.
  • Merging: O1 ⇒ O2; O1 ⇒ O3; 02 ⇒ O4; 03 ⇒ 04.

Finally, an articulation allows for defining a way in which the fusion or merging of ontologies has to be carried out. The intuitive idea is to construct the minimal union of vocabularies S1 and S2 and axioms A1 and A2 that respects the articulation, i.e., that is defined modulo the articulation (see Figure 1). This corresponds to the mathematical pushout construct, and is exploited, for instance, in the frameworks described in (Bench-Capon and Malcolm 1999; Kent 2000; Schorlemmer 2002). Again, this ‘strong’ notion of merging can be relaxed by taking the articulation of two sub-ontologies of O1 and O2 respectively, and defining the merged ontology O according to their articulation.

A word on translation and integration. Translation is used by different authors to describe two different things. First, there is the translation between formal languages, for example from Ontolingua to Prolog. This changes the syntactic structure of axioms, but not the vocabulary. This is not of our concern in this survey. Second, there is the actual translation of the vocabulary. This is intimately linked to the issue of ontology mapping. Actually, the difference between mapping and translation is that the former denotes the process of defining a collection of functions that specify which concepts and relations correspond to which other concepts and relation, while the latter is the application of the mapping functions to actually translate the sentences that use the one ontology into the other. This presupposes that the ontologies share the domain in which the respective vocabularies are interpreted. Under integration, on the other hand, we regard the composition of ontologies to build new ones, but whose respective vocabulary are usually not interpreted in the same domain of discourse.

4 Examples

Fern´andez-Breis and Mart´ınez-B´ejar: In Figure 5 we illustrate the example used in (Fern´andez-Breis and Mart´ınez-B´ejar 2002). As we reported in Section 3.a, Fern´andez-Breis and Mart´ınez-B´ejar developed an algorithm for integrating ontologies. The algorithm works as follows: it detects synonymous concepts (e.g., BUILDING, SCIENCES FACULTY in both ontologies), as well as exploits nodes in the hierarchy that have the same attributes. The upper part of Figure 5 illustrates two university ontologies describing a faculty of sciences, whereas the lower part illustrates the integrated ontology. The concept PEOPLE has been converted to PERSON since both concepts share the same attributes (AGE, INCOME). The algorithm also integrates attributes of the same concepts (BUILDING in the integrated ontology has the sum of its predecessors’ attributes in the original ontologies).

5 Pragmatics

In Sections 3 and 4 we have described and showed examples of 35 works related to ontology mapping. In this section we will elaborate on important topics that emerged when examining these works. We were selective in choosing the topics that we think are prevailing when practitioners are faced with the subtle task of ontology mapping. While the main section of this article aims to act as a road map of ontology mapping works today, herein, we critically review issues concerned with the relation of ontology mapping and databases schemata integration, the normalisation of ontologies and the creation of formal instances, the role of formal theory in support of ontology mapping, the use of heuristics, the use of articulation and mapping rules, the definition of semantic bridges, nd we also discuss the thorny issue of automated ontology mapping.

6 Conclusions

In this article we presented the state-of-the-art in ontology mapping: 35 works have been reviewed and some of them illustrated through example cases. Many more have been left out of this survey: It was not feasible neither practical to include everything that has been done to date. Rather, we selected indicative examples that characterise a range of related works.

We argue that ontology mapping nowadays faces some of the challenges we were facing ten years ago when the ontology field was at its infancy. We still do not understand completely the issues involved. However, the field evolves fast and attracts the attention of many practitioners among a variety of disciplines, the result being the variety of works we presented in this article. As today we know more about ontologies, how to design, develop, and deploy them. We hope that this article contributes to a better understanding of the emerging field of ontology mapping.

References

  • Serge Abiteboul, Sophie Cluet, Tova Milo, Correspondence and translation for heterogeneous data, Theoretical Computer Science, v.275 n.1-2, p.179-213, March 28 2002 doi:10.1016/S0304-3975(01)00128-1
  • AKT, 2001, "Advanced knowledge technologies interdisciplinary research collaboration" Technical Report, available at www.aktors.org/publications/Manifesto.doc.
  • Barr, M, 1996, "The Chu construction" Theory and Applications of Categories 2(2) 17-35.
  • Jon Barwise, Jerry Seligman, Information flow: the logic of distributed systems, Cambridge University Press, New York, NY, 1997
  • Trevor J. M. Bench-Capon, Grant Malcolm, Formalising Ontologies and Their Relations, Proceedings of the 10th International Conference on Database and Expert Systems Applications, p.250-259, August 30-September 03, 1999
  • Pim Borst, Hans Akkermans, Jan Top, Engineering ontologies, International Journal of Human-Computer Studies, v.46 n.2-3, p.365-406, Feb./March 1997 doi:10.1006/ijhc.1996.0096
  • Calvanese, D, De Giacomo, G and Lenzerini, M, 2001a, "A framework for ontology integration" Proceedings of the 1st Internationally Semantic Web Working Symposium (SWWS) 303-317.
  • Calvanese, D, De Giacomo, G and Lenzerini, M, 2001b "Ontology of integration and integration of ontologies" Proceedings of the 2001 International Description Logics Workshop (DL2001) 10-19.
  • Campbell, AE and Shapiro, SC, 1998, "Algorithms for ontological mediation" Technical Report 98-03, Department of Computer Science and Engineering, State University of New York at Buffalo.
  • Chalupksy, H, 2000, "OntoMorph: a translation system for symbolic knowledge Proceedings of the 17th International Conference on Knowledge Representation and Reasoning (KR-2000).
  • Compatangelo, E and Meisel, H, 2002, "Intelligent support to knowledge sharing through the articulation of class schemas" Proceedings of the 6th International Conference on Knowledge-based Intelligent Information & Engineering Systems (KES'02).
  • Corréa da Silva, F, Vasconcelos, W, Robertson, D, Brilhante, V, de Melo, A, Finger, M and Agustí, J, 2002, "On the insufficiency of ontologies: problems in knowledge sharing and alternative solutions" Knowledge-based Systems 15(3) 147-167.
  • AnHai Doan, Jayant Madhavan, Pedro Domingos, Alon Halevy, Learning to map between ontologies on the semantic web, Proceedings of the 11th International Conference on World Wide Web, May 07-11, 2002, Honolulu, Hawaii, USA doi:10.1145/511446.511532
  • Domingue, J, 1998, "Tadzebao and WebOnto: discussing, browsing, and editing ontologies on the Web" Proceedings of the 11th Knowledge Acquisition, Modelling and Management Workshop, KAW'98.
  • Enderton, H, 2001, A Mathematical Introduction to Logic Academic Press.
  • Adam Farquhar, Richard Fikes, James Rice, The Ontolingua Server: a tool for collaborative ontology construction, International Journal of Human-Computer Studies, v.46 n.6, p.707-727, June 1997 doi:10.1006/ijhc.1996.0121
  • Jesualdo Tomás Fernández-Breis, Rodrigo Martínez-Béjar, A cooperative framework for integrating ontologies, International Journal of Human-Computer Studies, v.56 n.6, p.665-720, June 2002 doi:10.1006/ijhc.1010
  • Bernhard Ganter, C. Franzke, Rudolf Wille, Formal Concept Analysis: Mathematical Foundations, Springer-Verlag New York, Inc., Secaucus, NJ, 1997
  • Genesereth, R and Fikes, R, 1992, "Knowledge interchange format" Technical Report, Logic-92-1, Computer Science Dept., Stanford University, 3.0 edition.
  • Grosso, W, Eriksson, H, Fergerson, R, Gennari, J, Tu, S and Musen, M, 1999, "Knowledge modelling at the millennium - the design and evolution of Protege2000" Proceedings of the 12th Knowledge Acquisition, Modelling, and Management (KAW'99).
  • Gruber, T and Olsen, G, 1994, "An ontology for engineering mathematics" Proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning 258-269.
  • Grüninger, M, 1997, "Ontologies for translation: notes for refugees from Babel" EIL Technical Report, Enterprise Integration Laboratory (EIL), University of Toronto, Canada.
  • Vineet Gupta, CHU spaces: a model of concurrency, Stanford University, Stanford, CA, 1994
  • Jannink, J, Pichai, S, Verheijen, D and Wiederhold, G. "Encapsulation and composition of ontologies" Proceedings of the AAAI'98 Workshop on Information Integration 43-51.
  • Yannis Kalfoglou, W. Marco Schorlemmer, Information-Flow-based Ontology Mapping, On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002, p.1132-1151, October 30-November 01, 2002
  • Kent, R, 2000, "The information flow foundation for conceptual knowledge organization" Proceedings of the 6th International Conference of the International Society for Knowledge Organization (ISKO).
  • Atanas Kiryakov, Kiril Iv. Simov, Marin Dimitrov, OntoMap: portal for upper-level ontologies, Proceedings of the International Conference on Formal Ontology in Information Systems, p.47-58, October 17-19, 2001, Ogunquit, Maine, USA doi:10.1145/505168.505174
  • Martin S. Lacher, Georg Groh, Facilitating the Exchange of Explicit Knowledge through Ontology Mappings, Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference, p.305-309, May 21-23, 2001
  • Lassila, O and Swick, R, 1999, "Resource description framework (RDF) model and syntax specification" W3C recommendation, W3C.
  • Jintae Lee, Michael Gruninger, Yan Jin, Thomas Malone, Austin Tate, Gregg Yost, Other Members Of The PIF Working Group, The Process Interchange Format and Framework, The Knowledge Engineering Review, v.13 n.1, p.91-120, March 1998 doi:10.1017/S0269888998001015
  • McGuinness, D, Fikes, R, Rice, J and Wilder, S, 2000, "An environment for merging and testing large ontologies" Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR-2000).
  • Jayant Madhavan, Philip A. Bernstein, Pedro Domingos, Alon Y. Halevy, Representing and reasoning about mappings between domain models, Eighteenth national conference on Artificial intelligence, p.80-86, July 28-August 01, 2002, Edmonton, Alberta, Canada
  • Maedche, A and Staab, S "Semi-automatic engineering of ontologies from texts" Proceedings of the 12th International Conference on Software Engineering and Knowledge Engineering (SEKE 2000) 231-239.
  • Mena, E, Kashyap, V, Illarramendi, A and Sheth, A, 1998, "Domain Specific Ontologies for Semantic Information Brokering on the Global Information Infrastructure" Proceedings of the 1st International Conference on Formal Ontology in Information Systems (FOIS'98) 269-283.
  • Meseguer, J, 1989, "General logics" Logic Colloquium '87 275-329.
  • Mitra, P and Wiederhold, G, 2002, "Resolving terminological heterogeneity in ontologies" Proceedings of the ECAI'02 workshop on Ontologies and Semantic Interoperability.
  • James W. Moore, Software Engineering Standards: A User's Road Map, IEEE Computer Society Press, Los Alamitos, CA, 1998
  • E. Motta, Reusable Components for Knowledge Modelling: Case Studies in Parametric Design Problem Solving, IOS Press, Amsterdam, The Netherlands, 1999
  • Noy, NF and Klein, M, 2002, "Ontology evolution: not the same as schema evolution" Also as: Smi-2002-0926, University of Stanford, Stanford Medical Informatics. Journal of Knowledge and Information Systems (In Press).
  • Noy, NF and Musen, M, 1999, "SMART: automated support for ontology merging and alignment" Proceedings of the 12th Workshop on Knowledge Acquisition, Modelling and Management (KAW'99).
  • Natalya Fridman Noy, Mark A. Musen, PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment, Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence, p.450-455, July 30-August 03, 2000
  • Natalya F. Noy, Mark A. Musen, Promptdiff: a fixed-point algorithm for comparing ontology versions, Eighteenth national conference on Artificial intelligence, p.744-750, July 28-August 01, 2002, Edmonton, Alberta, Canada
  • OntoWeb, 2002, "A survey on ontology tools" EU Thematic network, IST-2000-29243 Deliverable 1.3, OntoWeb - Ontology-based information exchange for knowledge management and electronic commerce, available at www.ontoweb.org/deliverable.htm.
  • Pinto, S, Gomez-Perez, A and Martins, J, 1999, "Some Issues on ontology integration" Proceedings of the IJCAI- 99 Workshop on Ontologies and Problem-Solving Methods (KRR5) 7.1-7.12.
  • Prasad, S, Peng, Y and Finin, T, 2002, "Using explicit information to map between two ontologies" Proceedings of the AAMAS 2002 Wokshop on Ontologies in Agent Systems (OAS'02) 52-57.
  • Vaughan R. Pratt, The Stone Gamut: A Coordinatization of Mathematics, Proceedings of the 10th Annual IEEE Symposium on Logic in Computer Science, p.444, June 26-29, 1995
  • Priss, U, 2001 "A Triadic Model of Information Flow" Proceedings of the 9th International Conference on Conceptual Structures (ICCS'01) 159-171.
  • Erhard Rahm, Philip A. Bernstein, A survey of approaches to automatic schema matching, The VLDB Journal — The International Journal on Very Large Data Bases, v.10 n.4, p.334-350, December 2001 doi:10.1007/s007780100057
  • Reed, S and Lenat, D, 2002, "Mapping ontologies into CyC" Proceedings of the AAAI'02 workshop on Ontologies and the Semantic Web 1-7.
  • Schorlemmer, M, 2002, "Duality in knowledge sharing" Proceedings of the Seventh International Symposium on Artificial Intelligence and Mathematics.
  • Guus T. Schreiber, Hans Akkermans, Knowledge engineering and management: the CommonKADS methodology, MIT Press, Cambridge, MA, 2000
  • Edward Sciore, Michael Siegel, Arnon Rosenthal, Using semantic values to facilitate interoperability among heterogeneous information systems, ACM Transactions on Database Systems (TODS), v.19 n.2, p.254-290, June 1994 doi:10.1145/176567.176570
  • Amit P. Sheth, James A. Larson, Federated database systems for managing distributed, heterogeneous, and autonomous databases, ACM Computing Surveys (CSUR), v.22 n.3, p.183-236, Sept. 1990 doi:10.1145/96602.96604
  • J. F. Sowa, Conceptual structures: information processing in mind and machine, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1984
  • Stumme, G and Maedche, A, 2001, "Ontology merging for federated ontologies on the semantic web" Proceedings of the International Workshop for Foundations of Models for Information Integration (FMII- 2001).
  • Uschold, M, Healy, M, Williamson, K, Clark, P and Woods, S, 1998, "Ontology reuse and application" Proceedings of the 1st International Conference on Formal Ontology in Information Systems(FOIS'98) 179-192.
  • Visser, P and Tamma, V, 1999, "An experiment with ontology-based agent clustering" Proceedings of the IJCAI- 99 Workshop on Ontologies and Problem-Solving Methods 12.1-12.13.
  • Visser, PRS, Jones, DM, Bench-Capon, TJM and Shave, MJR, 1998, "Assessing heterogeneity by classifying ontology mismatches" Proceedings of 1st International Conference on Formal Ontologies in Information Systems, FOIS'98 148-162.,


 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2003 OntologyMappingStateofTheArtYannis Kalfoglou
Marco Schorlemmer
Namyoun Choi
Ontology Mapping: the State of the ArtThe Knowledge Engineering Reviewhttp://eprints.ecs.soton.ac.uk/10519/1/ker02-ontomap.pdf10.1017/S02698889030006512003