| dc.description.abstract | Semantic interoperability represents the capability of two or more systems to
meaningfully and accurately interpret the exchanged data so as to produce
useful results. It is an essential feature of all distributed and open knowledge
based systems designed for both e-government and private businesses, since it
enables machine interpretation, inferencing and computable logic.
Unfortunately, the task of achieving semantic interoperability is very difficult
because it requires that the meanings of any data must be specified in an
appropriate detail in order to resolve any potential ambiguity.
Currently, the best technology recognized for achieving such level of precision
in specification of meaning is represented by ontologies. According to the
most frequently referenced definition [1], an ontology is an explicit
specification of a conceptualization, i.e., the formal specification of the
objects, concepts, and other entities that are presumed to exist in some area of
interest and the relationships that hold them [2]. However, different tasks or
different points of view lead ontology designers to produce different
conceptualizations of the same domain of interest. This means that the
subjectivity of the ontology modeling results in the creation of heterogeneous
ontologies characterized by terminological and conceptual discrepancies.
Examples of these discrepancies are the use of different words to name the
same concept, the use of the same word to name different concepts, the
creation of hierarchies for a specific domain region with different levels of
detail and so on. The arising so-called semantic heterogeneity problem
represents, in turn, an obstacle for achieving semantic interoperability... [edited by author] | en_US |
