"Vagueness is a common human knowledge and language phenomenon, typically manifested by terms and concepts like High, Expert, Bad, Near, etc. It is a phenomenon related to our inability to precisely determine the extensions of such concepts in certain domains and contexts. That is because vague concepts have typically blurred boundaries which do not allow for a sharp distinction between the entities that fall within their extension and those that do no. For example, some people are borderline tall: not clearly 'tall' and not clearly 'not tall'.
In an OWL ontology vagueness may primarily appear in the definitions of classes, object and datatype properties, and datatypes. A class is vague if, in the given domain, context or application scenario, it admits borderline cases, namely if there are (or could be) individuals for which it is indeterminate whether they instantiate the class. Typical vague classes are attributions, namely classes that reflect qualitative states of entities (e.g., TallPerson, ExperiencedResearcher etc.). Similarly, an object property (relation) is vague if there are (or could be) pairs of individuals for which it is indeterminate whether they stand in the relation (e.g., hasGenre, hasIdeology etc.). The same applies for datatype properties and pairs of individuals and literal values. Finally, a vague datatype consists of a set of vague terms. An example is the datatype RestaurantPriceRange when this comprises the terms 'cheap', 'moderate' and 'expensive'.
The Vagueness Ontology enables the explicit identification and description of vague entities and (some of) their vagueness-related characteristics in OWL ontologies. Such a description is to be made by ontology creators and its goal is the narrowing of the possible interpretations that its vague entities may assume by human and software agents."