An approximation to the computational theory of perceptions using ontologies

New technologies allow users to access huge amounts of data about phenomena in their environment. Nevertheless, linguistic description of these available data requires that human experts interpret them highlighting the relevant details and hiding the irrelevant ones. Experts use their personal experience on the described phenomenon and in using the flexibility of natural language to create their reports. In the research line of Computing with Words and Perceptions, this paper deals with the challenge of using ontologies to create a computational representation of the expert’s knowledge including his/her experience on both the context of the analyzed phenomenon and his/her personal use of language in that specific context. The proposed representation takes as basis the Granular Linguistic Model of a Phenomenon previously proposed by two of the authors. Our approach is explained and demonstrated using a series of practical prototypes with increasing degree of complexity.