20182018 2nd International Conference on Inventive Systems and Control (ICISC)Requires access

A review on metrics for ontology evaluation

Ravi Lourdusamy, Antony John

Open publisher page 38 citations

Abstract

Ontology helps semantic systems to establish a model of the world in order to derive machine processed knowledge. It represents formally the concepts, objects, properties and establishes the relationship between them. By providing the structure and semantics for data representation ontology has opened an avenue for appropriate representation of the world for specific and explicit sharing of knowledge without ambiguities. The use of ontology in various applications and the availability of ontology on the web have increased. Ontology should be evaluated from various perspectives to determine the quality of ontology before use or reuse. Ontology evaluation is one of the key phases in ontology development. The ontology should be accurate and provide the accurate results to a user. Unless the quality of the ontology is assured the accuracy of the results cannot be guaranteed. Metrics is used to measure the quality of ontology from different dimensions. This paper explores various metrics used for ontology evaluation and investigates the underlying mechanisms.

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What this paper is about

Ontology helps semantic systems to establish a model of the world in order to derive machine processed knowledge. It represents formally the concepts, objects, properties and establishes the relationship between them. By providing the structure and semantics for data representation ontology has opened an avenue for appropriate representation of the world for specific and explicit sharing of knowledge without ambiguities. The use of ontology in various applications and the availability of ontology on the web have increased. Ontology should be evaluated from various perspectives to determine the quality of ontology before use or reuse. Ontology evaluation is one of the key phases in ontology development. The ontology should be accurate and provide the accurate results to a user. Unless the quality of the ontology is assured the accuracy of the results cannot be guaranteed. Metrics is used to measure the quality of ontology from different dimensions. This paper explores various metrics used for ontology evaluation and investigates the underlying mechanisms.

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OpenAlex reports 38 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Ontology helps semantic systems to establish a model of the world in order to derive machine processed knowledge. It represents formally the concepts, objects, properties and establishes the relationship between them. By providing the structure and semantics for data representation ontology has opened an avenue for appropriate representation of the world for specific and explicit sharing of knowledge without ambiguities. The use of ontology in various applications and the availability of ontology on the web have increased. Ontology should be evaluated from various perspectives to determine the quality of ontology before use or reuse. Ontology evaluation is one of the key phases in ontology development. The ontology should be accurate and provide the accurate results to a user. Unless the quality of the ontology is assured the accuracy of the results cannot be guaranteed. Metrics is used to measure the quality of ontology from different dimensions. This paper explores various metrics used for ontology evaluation and investigates the underlying mechanisms.

Key concepts: Ontology, Computer science, Upper ontology, Ontology-based data integration, Process ontology, Suggested Upper Merged Ontology, Ontology Inference Layer, Ontology alignment

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