Abstract
Web ontology language (OWL) is one of the last recommendations from the World Wide Web Consortium (W3C) to develop ontologies. The use of OWL ontologies must involve the possibility of the evaluation of quality and correctness. A wide diversity of tools and metrics has been proposed to reach this goal. ONTOMETRIC, OntoQA and Protégé represent the most important tools to evaluate ontologies that usually support metrics. This paper analyses all these tools and makes a proposal to normalize the ontology metrics as a pre-process to apply structural metrics. Also, an OWL-VisMod instrument is introduced as a visual modeling tool with capabilities of metric calculation, especially metrics related to semantics. Nevertheless, it also includes metrics for the schema such as diverse counters for subclasses, object and data type properties and individuals. Finally, diverse visualisations targeted to represent the proposed metrics are included. Key words: Ontology metrics, ontology construction support tools, ontology visualization, web ontology language, web ontology language -VisMod.
Highlights
An ontology formally describes a domain of discourse
Diverse ontology metrics and tools have been analysed, most of them are focused on the evaluation of the ontologies structure such as „protégé‟, „ontology metrics‟ tool or OntoQA
Other metrics are focused on cohesion such as number of root classes (NoR), number of leaf classes (NoL), ADIT-LN, number of ontology partitions (NOP), number of minimally inconsistent subsets (NMIS), average value of axiom inconsistencies (AVAI) and OntoQA, and there are a few of them focused on coupling such as number of external classes (NEC), references to external classes (REC), referenced includes (RI) and CBE proposals
Summary
An ontology formally describes a domain of discourse. Typically, an ontology consists of a finite list of terms and the relationships among these terms. Ontology metrics represent an important approach because of the fact that they can help assess and qualify an ontology. Metrics are useful in the process of whether or not to reuse an ontology because before using a previously defined ontology it would be desirable to evaluate it in order to determine the value of using it again. Metrics should always be taken into account when evaluating ontologies both during the engineering and application processes. Most metrics are defined from empirical analysis and after being tested with real ontologies they are evaluated. Some approaches taken from the „software engineering field‟ have been adapted and used in the ontologies field
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