Authors:
Achim Reiz
and
Kurt Sandkuhl
Affiliation:
Rostock University, 18051 Rostock, Germany
Keyword(s):
Ontology Metrics, NEOntometrics, Ontology Quality, OntoMetrics, Knowledge Engineering.
Abstract:
Ontologies are the glue for the semantic web, knowledge graphs, and rule-based intelligence in general. They build on description logic, and their development is a non-trivial task. The underlying complexity emphasizes the need for quality control, and one way to measure ontologies is through ontology metrics. For a long time, the calculation of ontology metrics was merely a theoretical proposal: While there was no shortage of proposed ontology metrics, actual applications were mostly missing. That changed with the creation of NEOntometrics, a tool that implemented the majority of ontology metrics proposed in the literature. While it is now possible to calculate large amounts of ontology metrics, it also revealed that the calculation alone does not make the metrics useful (yet). In NEOntometrics alone, there are over 160 ontology metrics – a careful selection for the given use case is crucial. This position paper argues for a selection process for ontology metrics. It first presents
core questions for identifying the underlying ontology requirements and then guides users to identify the correct attributes and their associated measures.
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