Semantic Web-Based Information Systems: State-of-the-Art ...

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Bu ld ng Ontology Translat on Systems of the transformations have been implemented in formal languages, most of the processes involved in this task can be automated. If problems are detected during this task, the method recommends going back to the implementation activities in order to solve them. Finally, the method proposes to execute the test suite that was defined during the analysis activity, which is considered the system tests for our system. This does not prevent us from defining and executing other kinds of tests (from unitary tests to integration tests) at any point during the development. This task consists of inputting the ontologies in the test suite to the resulting ontology translation system and checking whether the output corresponds to the one expected. Note that in most cases, this check will consist of comparing whether the output file(s) and the expected file(s) are identical, but there are cases where this kind of comparison will not be possible, since the results can come in any order (e.g., in RDF and OWL ontologies). If any of the test fails, we must go back to the previous implementation activities to detect the problems. Furthermore, we must consider that the method allows moving to previous activities if problems are detected at any point of our development. Conclusion This chapter presents two important contributions to the current state of the art on ontology translation. First, it proposes to consider that ontology translation problems can appear at four different layers, which are interrelated, and can describe the most common problems that may appear at each of those layers. Some existing approaches have identified similar layers in ontology translation. However, these and other approaches have focused mainly on the problems related to the semantic layer and have not considered the other ones, which are also important for building systems that make good quality translations. The low quality of some translation systems has been shown recently in the interoperability experiment performed for the ISWC2003 workshop on Evaluation of Ontology Tools. 6 The results obtained in this workshop showed that making good translation decisions at the lexical, syntax, and pragmatic levels is also as important as making good translation decisions at the semantic level. The second main contribution of this chapter is related to the fact that it is the first approach that gives an integrated support for the complex task of building ontology translation systems. As we commented in the introduction, ontology translation systems are not easy to create and are difficult to maintain, as well. Most of the translation systems currently available have been developed ad hoc; the translation decisions that they implement are usually difficult to understand and hidden in the source code of the systems; and, in addition, it is neither clear nor documented how Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
Corcho & Gómez-Pérez much knowledge is lost in the transformations that they perform. There are many complex decisions that have to be implemented, and these decisions are usually taken at the low implementation level instead of performing a detailed analysis and design of the different translation choices available and taking a decision based on the actual ontology translation requirements. The method proposed in this chapter helps in this task by identifying clearly the activities to be performed, the tasks in which each activity is decomposed, how these tasks have to be performed, the inputs and outputs of the activities, and the set of techniques that can be used to perform them. Moreover, a set of declarative languages is proposed, although not described in this chapter, to help in the implementation of translation decisions. This method has been derived from our long experience in the generation of ontology translation systems from the ontology engineering platform WebODE to different ontology languages and tools, and vice versa (12 systems), and has been used for building other six ontology translation systems. These systems have been built successfully by different people with backgrounds in knowledge and software engineering, following the method proposed in this chapter and the techniques identified for each task. Related.Work Although there are no other integrated methods for building ontology translation systems available, we can find some technology that allows creating them. Specifically, we can cite two tools: Transmorpher and OntoMorph: • Transmorpher 7 (Euzenat & Tardif, 2001) is a tool that facilitates the definition and processing of complex transformations of XML documents. Among other domains, this tool has been used in the context of ontologies, using a set of XSLT documents that is able to transform from one DL language to another, expressed in DLML. 8 This tool is aimed at supporting the “family of ontology languages” approach for ontology translation described in Euzenat and Stuckenschmidt (2003). The main limitation of this approach is that it only deals with problems in the semantic layer and does not focus on other problems related to the lexical, syntax, and pragmatic layers. • OntoMorph (Chalupsky, 2000) is a tool that allows creating translators declaratively. Transformations between the source and target formats are specified by means of pattern-based transformation rules and are performed in two phases: syntactic rewriting and semantic rewriting. The last one needs the ontology or part of it translated into PowerLoom, so that this KR system can be used for certain kinds of reasoning, such as discovering whether a class is a subclass Copyright © 2007, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited.
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Chapter.VIII Querying.the.Web.Recon
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the semantics in the Semantic Web.
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the conventional Web, and the emerg
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About.the.Authors About the Authors
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About the Authors 0 Veli. Bicer. is
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About the Authors 0 in refereed jou
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About the Authors 0 partment (1992)
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About the Authors Anton.Naumenko.is
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consumer-centric business model 30
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semantic e-business 214 semantic in
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