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.

Schema/ontology matching is a critical problem in many application domains, such as, semantic web, schema/ontology integration, data warehouses, e-commerce, catalog matching, etc. Many diverse solutions to the matching problem have been proposed so far. In this paper we present a taxonomy of schema-based matching techniques that builds on the previous work on classifying schema matching approaches. Some innovations are in introducing new criteria which distinguish between matching techniques relying on diverse semantic clues. In particular, we distinguish between heuristic and formal techniques at schemalevel; and implicit and explicit techniques at element- and structure-level. Based on the classification proposed we overview some of the recent schema/ontology matching systems pointing which part of the solution space they cover.

Support for ontology evolution becomes extremely important in distributed development and use of ontologies. A component-base approach can lead us to a distrubuted ontology.

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Ontology is increasingly seen as a key factor for enabling interoperability across heterogeneous systems and semantic web applications. Ontology mapping is required for combining distributed and heterogeneous ontologies. Developing such ontology mapping has been a core issue of recent ontology research. This paper presents ontology mapping categories, describes the characteristics of each category, compares these characteristics, and surveys tools, systems, and related work based on each category of ontology mapping. We believe this paper provides readers with a comprehensive understanding of ontology mapping and points to various research topics about the specific roles of ontology mapping.

In this paper we describe a plug-in (OntoLT) for the widely used Protégé ontology development tool that supports the interactive extraction and/or extension of ontologies from text. The OntoLT approach provides an environment for the integration of linguistic analysis in ontology engineering through the definition of mapping rules that map linguistic entities in annotated text collections to concept and attribute candidates (i.e. Protégé classes and slots). The paper explains this approach in more detail and discusses some initial experiments on deriving a shallow ontology for the neurology domain from a corresponding collection of neurological scientific abstracts. 1

Currently, computers are changing from single, isolated devices into entry points to a worldwide network of information exchange and business transactions called the World Wide Web (WWW). For this reason, support in data, information, and knowledge exchange has become a key issue in current computer technology. The success of the WWW has made it increasingly difficult to find, access, present, and maintain the information required by a wide variety of users. In response to this problem, many new research initiatives and commercial enterprises have been set up to enrich available information with machine processable semantics. This semantic web will provide intelligent access to heterogeneous, distributed information, enabling software products (agents) to mediate between user needs and the information sources available. This paper summarizes ongoing research in the area of the semantic web, focusing especially on ontology technology.

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Case Study Purpose: The ontology engineering methodology DILIGENT is presented, a methodology focussing on the evolution of ontologies instead of the initial design, thus recognizing that knowledge is a tangible and moving target.

Ontologies evolve when the underlying domain world changes at different points of time. The result then is a series of ontologies whose concepts are related with each other not only within one ontology valid at a moment but through the time, too. This chapter presents a model for representing ontology time series. The focus is on modeling partial overlap between concepts evolving over long periods of time, and the domain of application is historical geospatial reasoning. A framework is presented for representing and reasoning about conceptual overlap of concepts that evolve over an ontology time series. The idea is to provide the ontology developer with an intuitive change ontology for expressing local ontological changes in a declarative way. An algorithm is presented for reasoning about overlapping concepts globally over long periods of time. This algorithm can be applied, e.g., in concept-based information retrieval for ranking search results according to their relevance.