In this post I try to cover the research issues and open problems of Semantic Web with respect to approximation and especially approximate reasoning.
There are a few number of researches in literature and in my point of view they are far from practical applications. One of the most interesting issues for me is considering fuzziness in Description Logics (DLs) for ontologies. Pavel and Lawrence discuss this in "Fuzzy Rough Approach to Handling Imprecision in Semantic Web Ontologies". This paper introduces the way that rough set methods can handle uncertainty in DLs.
Bartley and Lawrence discuss merging ontologies to reach a single ontology using beyes's theorem "Approximate Metrics For Autonomous Semantic Web Ontology Merging". In addition to each ontology they use a thesaurus of that ontology to "specify the acceptable values for merging" within their architecture.
In conclusion since many languages such as OWL DL are based on DLs (OWL DL is based on SHOIN(D)) therefore I believe that a better understanding of DLs is indispensable for Semantic Web researchers.
