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.

In order to tackle the need of sharing knowledge within and across organisational boundaries, the last decade has seen researchers both in academia and industry advocating for the use of ontologies as a means for providing a shared understanding of common domains. But with the generalised use of large distributed environments such as the World Wide Web came the proliferation of many di#erent ontologies, even for the same or similar domain, hence setting forth a new need of sharing---that of sharing ontologies. In addition, if visions such as the Semantic Web are ever going to become a reality, it will be necessary to provide as much automated support as possible to the task of mapping di#erent ontologies. Although many e#orts in ontology mapping have already been carried out, we have noticed that few of them are based on strong theoretical grounds and on principled methodologies. Furthermore, many of them are based only on syntactical criteria. In this paper we present a theory and method for automated ontology mapping based on channel theory, a mathematical theory of semantic information flow.

As ontologies become ever more important for semanticallyrich information exchange and a crucial element for supporting knowledge sharing in a large distributed environment, like the Web, the demand for sharing them increases accordingly. One way of achieving this ambitious goal is to provide mechanised ways for mapping and merging ontologies. This has been the focus of recent research in knowledge engineering.

We elaborate on the mathematical foundations of the meaning coordination problem that agents face in open environments. We investigate to which extend the Barwise-Seligman theory of information flow provides a faithful theoretical description of the partial semantic integration that two agents achieve as they progressively align their underlying ontologies through the sharing of tokens, such as instances. We also discuss the insights and practical implications of the Barwise-Seligman theory with respect to the general meaning coordination problem.

Any builder of an information system, whether a database or a knowledge based system, will start from some conceptualisation of the domain, which will embody a number of fundamental assumptions about the domain. Often these underlying assumptions...

Abstract. We address the mathematical foundations of the ontology coordination problem and investigate to which extend the Barwise-Seligman theory of information flow may provide a faithful theoretical description of the problem. We give a formalisation of the coordination of populated ontologies based on instance exchange that captures progressive partial semantic integration. We also discuss the insights that the Barwise-Seligman theory provides to the general ontology coordination problem. 1

In order to address problems stemming from the dynamic nature of distributed systems, there is a need to be able to express the often neglected notions of the evolution and change of the knowledge components of such systems. This need becomes more pressing when one considers the potential of the Internet for distributed knowledge-based problem solving — and the pragmatic issues surrounding knowledge integrity. In this paper, we introduce a formal calculus for describing transformations in the ‘life cycles ’ of knowledge components, along with ideas about the nature of distributed environments in which the ideas underpinning the calculus can be realised. The formality and level of abstraction of this language encourage the analysis of knowledge histories and allows useful properties about this knowledge to be inferred. These ideas are illustrated through the discussion of a particular case-study in knowledge evolution. 1