The CIDOC CRM, an Ontological Approach to Schema Heterogeneity

The CIDOC Conceptual Reference Model (CRM), now ISO/CD21127, is a core ontology that aims at enabling information exchange and integration between heterogeneous sources of cultural heritage information, archives and libraries. It provides semantic definitions and clarifications needed to transform disparate, heterogeneous information sources into a coherent global resource, be it within a larger institution, in intranets or on the Internet. It is argued that such an ontology is property-centric, compact and highly generic, in contrast to terminological systems. The presentation will demonstrate how such a well-crafted core ontology can help to achieve a very high precision of schema integration at reasonable cost in a huge, diverse domain. It is further argued that such ontologies are widely reusable and adaptable to other domains which makes their development cost effective

Ontology Mapping: The State of the Art

Ontology mapping is seen as a solution provider in today\u27s 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 mapping has beeb 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

Ontology Alignment: An annotated Bibliography

Ontology mapping, alignment, and translation has been an active research component of the general research on semantic integration and interoperability. In our talk, we gave our own classification of different topics in this research. We talked about types of heterogeneity between ontologies, various mapping representations, classified methods for discovering methods both between ontology concepts and data, and talked about various tasks where mappings are used. In this extended abstract of our talk, we provide an annotated bibliography for this area of research, giving readers brief pointers on representative papers in each of the topics mentioned above. We did not attempt to compile a comprehensive bibliography and hence the list in this abstract is necessarily incomplete. Rather, we tried to sketch a map of the field, with some specific reference to help interested readers in their exploration of the work to-date

S-Match: an algorithm and an implementation of semantic matching

We think of Match as an operator which takes two graph-like structures and produces a mapping between those nodes of the two graphs that correspond semantically to each other. Semantic matching is a novel approach where semantic correspondences are discovered by computing and returning as a result, the semantic information implicitly or explicitly codified in the labels of nodes and arcs. In this paper we present an algorithm implementing semantic matching, and we discuss its implementation within the S-Match system. We also test S-Match against three state of the art matching systems. The results, though preliminary, look promising, in particular for what concerns precision and recall

Ontology Merging with Formal Concept Analysis

In this short paper, we summarize two methods for merging ontologies: FCA-Merge and OntEx. Both methods are based on Formal Concept Analysis