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Abstract

Ontologies need to be stored, sometimes aligned and their evolution needs to be managed. All these tasks together are called ontology management. Alignment is a central task in ontology re-use. Re-use of existing ontologies often requires considerable effort: the ontologies either need to be integrated, which means that they are merged into one new ontology, or the ontologies can be kept separate. In both cases, the ontologies have to be aligned, which means that they have to be brought into mutual agreement. The problems that underlie the difficulties in integrating and aligning are the mismatches that may exist between separate ontologies. Ontologies can differ at the language level, which can mean that they are represented in a different syntax, or that the expressiveness of the ontology language is dissimilar. Ontologies also can have mismatches at the model level, for example, in the paradigm, or modelling style. Ontology alignment is very relevant in a Semantic Web context. The Semantic Web will provide us with a lot of freely accessible domain specific ontologies. To form a real web of semantics - which will allow computers to combine and infer implicit knowledge - those separate ontologies should be aligned and linked.
Support for evolving ontologies is required in almost all situations where ontologies are used in real-world applications. In those cases, ontologies are often developed by several persons and will continue to evolve over time, because of changes in the real world, adaptations to different tasks, or alignments to other ontologies. To prevent that such changes will invalidate existing usage, a change management methodology is needed. This involves advanced versioning methods for the development and the maintenance of ontologies, but also configuration management, that takes care of the identification, relations and interpretation of ontology versions. All these aspects come together in integrated ontology library systems. When the number of different ontologies is increasing, the task of storing, maintaining and re-organizing them to secure the successful re-use of ontologies is challenging. Ontology library systems can help in the grouping and reorganizing ontologies for further re-use, integration, maintenance, mapping and versioning. Basically, a library system offers various functions for managing, adapting and standardizing groups of ontologies. Such integrated systems are a requirement for the Semantic Web to grow further and scale up. In this chapter, we describe a number of results with respect to the above mentioned areas. We start with a description of the alignment task and show a meta-ontology that is developed to specify the mappings. Then, we discuss the problems that are caused by evolving ontologies and describe two important elements of a change management methodology. Finally, in Section 4.4 we survey existing library systems and formulate a wish-list of features of an ontology library system.

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a

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Abstract

Over the past few years, we have seen a growing interest in the potential of both peer-to-peer (P2P) computing and the use of more formal approaches to knowledge management, involving the development of ontologies. This penultimate chapter discusses possibilities that both approaches may offer for more effective and efficient knowledge management. In particular, we investigate how the two paradigms may be combined. In this chapter, we describe our vision in terms of a set of future steps that need to be taken to bring the results described in earlier chapters to their full potential.

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Abstract

This entry introduces ontologies as a potential "silver bullet" for knowledge management, enterprise application integration, and e-commerce. Ontologies enable knowledge sharing and knowledge reuse. The degree to which an ontology is machine-understandable, its formality, is determined by the language used for the specification of the ontology. There exists a trade-off between the expressiveness of an ontology language and the modeling support it provides for the ontology developer. This entry also describes how different knowledge representation formalisms, together with the Web languages XML and RDF, have influenced the development of the Web ontology language OWL.

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