Service Communautaire d'Information sur la Recherche et le Développement - CORDIS

Ontology methodologies

The need for reliable ontologies in the Semantic Web (SW) has risen two complementary issues that require the development of strong methodologies for ontology development. On the one hand, researchers are constructing new complex foundational ontologies to answer the demand for knowledge structures matching specific views of the world. On the other hand, the management of data and documents already available on the web requires a quite rich number of domain ontologies which should be clear and easily understood by the users.

Relatively to the first issue, we have recognized two main distinctions in deveolping foundational ontologies: the descriptive vs. revisionary attitude, and the multiplicative vs. reductionist attitude.

A descriptive ontology aims at describing the ontological assumptions behind language and cognition by taking seriously the surface structure of natural language and commonsense. A revisionary ontology, on the other hand, gives less importance to linguistic and cognitive aspects, and does not hesitate to suggest paraphrases of linguistic expressions or re-interpretations of cognitive phenomena in order to avoid ontological assumptions considered debatable on scientific grounds.

Regarding the second distinction, we observed and clarified that a reductionist ontology aims at describing a great number of ontological differences with the smallest number of concepts while in a multiplicative ontology expressivity is more relevant: the aim is to give a reliable account of reality despite of the need of a larger number of basic concepts.

Once these distinctions are recognized, we have isolated major notions that mark the ontological character of a foundational ontology.

These notions can be collected in four major groups, namely;
- Universals, particulars and individual properties,
- Abstract and concrete entities,
- endurants and perdurants, and
- Co-localized entities.

A strong methodology in the construction of foundational ontologies must include the crucial distinctions we listed above in this way making the developer aware of their consequences.

As it was recalled above, the other issue central to methodology is the development of domain ontologies for the SW. Several strategies have been exploited: machine learning, NLP techniques, semantic services, lifting existing metadata, etc. These strategies have different advantages according to the type of documents or domains: machine learning and NLP techniques try to extract useful recurrent patterns out of existing documents, and semantic services try to generate semantically indexed, structured documents e.g. out of transactions, existing metadata can be considered proto-ontologies that can be "lifted" from legacy indexing tools and indexed documents. In other words, metadata lifting ultimately tries to reengineer existing document management systems into dedicated semantic webs.

Legacy information systems often use metadata contained in Knowledge Organization Systems (KOSes), such as vocabularies, taxonomies and directories, in order to manage and organize information. KOSes support document tagging (thesaurus-based indexing) and information retrieval (thesaurus-based search), but their semantic informality and heterogeneity usually prevent a satisfactory integration of the supported documentary repositories and databases.

As a matter of fact, traditional techniques mainly consist of time-consuming, manual mappings that are made each time a new source or a modification enter the lifecycle by experts with idiosyncratic procedures. Informality and heterogeneity make them particularly hostile with reference to the SW.

In this case, our work concentrated on a demonstration of KOS reengineering issues from the viewpoint of formal ontology, therefore the main threads were given in the context of a concrete case study description rather than as explicitly addressed topics. In this work, we described the methodology used for the creation, integration and utilization of ontologies for information integration and semantic interoperability in a specific domain.

We expect that the clarifications and the examples provided on this topic will increase the reliability of the new foundational and domain ontologies. Furthermore, the overall discussion should increase the understanding of what ontologies are and how they may be classified according to their overall ontological structure.

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Institute for Cognitive Sciences and Technologies
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