Even though a few architectures exist to support the difficult ontology matching task, it happens often they are not reconfigurable (or just a little) related to both ontology features and applications needs. We introduce GENOMA, an architecture supporting development of Ontology Matching (OM) tools with the aims to reuse, possibly, existing modules each of them dealing with a specific task/sub...

The inherent heterogeneity of datasets on the Semantic Web has created a need to interlink them, and several tools have emerged that automate this task. In this paper we are interested in what happens if we enrich these matching tools with knowledge of the domain of the ontologies. We explore how to express the notion of a domain in terms usable for an ontology matching tool, and we examine var...

Ontologies are increasingly used to semantically categorize data and content. Hence there is an increasing need to match (align) and merge related ontologies, e. g., for data integration or enhanced data analysis. Semi-automatic ontology matching has been an active research area in the last decade and many tools have been developed. The benchmark results of the OAEI (Ontology Alignment Evaluati...

Ontologies are increasingly used to semantically categorize data and content. Hence there is an increasing need to match (align) and merge related ontologies, e. g., for data integration or enhanced data analysis. Semi-automatic ontology matching has been an active research area in the last decade and many tools have been developed. The benchmark results of the OAEI (Ontology Alignment Evaluati...

Current matching algorithms cannot be optimally used in ontology matching tasks as envisioned by the Semantic Web community, mainly because of the inherent dependency between approaches and ontology properties. As one possible solution we propose a Metadata-based Ontology MAtching (MOMA) framework based on a reuse-paradigm that, given a set of ontologies to be matched, takes into account the ca...

Ontology Matching is a task needed in various applications, for example for comparison or merging purposes. In literature, many algorithms solving the matching problem can be found, but most of them do not consider instances at all. Mappings are determined by calculating the string-similarity of labels, by recognizing linguistic word relations (synonyms, subsumptions etc.) or by analyzing the (...