Abstract. You can only control what you can measure. Measuring ontologies is necessary to evaluate ontologies both during engineering and application. Metrics allow the fast and simple assessment of an ontology and also to track their subsequent evolution. In the last few years, a growing number of ontology metrics and measures have been suggested and defined. But many of them suffer from a recurring set of problems, most importantly they do not take the semantics of the ontology language properly into account. The work presented here is a principal approach to facilitate the creation of ontology metrics with the clear goal to go beyond structural metrics to proper semantic-aware ontology metrics. We have developed guidelines and a set of methodological tools based on the notions of "normalization" and "stable metrics" for creating ontology metrics. These guidelines allow the metric author to decide which properties metrics need to fulfil and to appropriately design the desired metric. A discussion of an exemplary metric (taken from literature) illustrates and motivates the issues and suggested solutions.
In one of the first approaches to analysing this implicit structure of ontologies, Vrandecic et al. REF introduce ontology metrics that also consider the semantics of the ontology language, mainly focusing on the entailed statements of an ontology.
How to Design Better Ontology Metrics
ESWC
Computer Science