Representing fuzzy ontologies in OWL 2

Abstract

The need to deal with vague information in Semantic Web languages is rising in importance and, thus, calls for a standard way to represent such information. We may address this issue by either extending current Semantic Web languages to cope with vagueness, or by providing a procedure to represent such information within current Semantic Web languages. In this work, we follow the latter approach, by identifying the syntactic differences that a fuzzy ontology language has to cope with, and by proposing a concrete methodology to represent fuzzy ontologies using OWL 2 annotation properties. I. INTRODUCTIONIt is widely agreed that classical ontology languages are not appropriate to deal with vagueness or imprecision in the knowledge, which is inherent to most of the real world application domains [19]. Since fuzzy set theory and fuzzy logic [21] are suitable formalisms to handle these types of knowledge, fuzzy ontologies emerge as useful in several applications, ranging from (multimedia) information retrieval to image interpretation, ontology mapping, matchmaking, decision making, or the Semantic Web.Description Logics (DLs) are the basis of several ontology languages. The current standard for ontology representation is OWL (Web Ontology Language), which comprises three sublanguages (OWL Lite, OWL DL and OWL Full). OWL 2 is a recent W3C recommendation [11]. The logical counterparts of OWL Lite, OWL DL and OWL 2 are the DLs SHIF(D), SHOIN (D), and SROIQ(D), respectively.Several fuzzy extensions of DLs can be found in the literature (see the survey in [10]) and some fuzzy DL reasoners have been implemented, such as FUZZYDL [4], DELOREAN [1] and FIRE [12]. Not surprisingly, each reasoner uses its own fuzzy DL language for representing fuzzy ontologies and, thus, there is a need for a standard way to represent such information.In this work, as we do not expect a fuzzy OWL extension to become a W3C proposed standard in the near future, we identify the syntactic differences that a fuzzy ontology language has to cope with, and propose to use OWL 2 itself to represent fuzzy ontologies. More precisely, we use OWL 2 annotation properties to encode fuzzy SROIQ(D) ontologies. The use of annotation properties makes possible (i) to use current OWL 2 editors for fuzzy ontology representation, and (ii) that OWL 2 reasoners discard the fuzzy part of a fuzzy ontology, producing the same results as if would not exist.The remainder of this paper is organized as follows. In Section II we present a fuzzy extension of DL SROIQ(D),

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