Hi Alexandre, In the field of Linked Data we cannot only talk of ontology matching or instance matching as separate fields, in my opinion its something in the middle, as you mostly have to check predicates, properties and class but also match the instance values if you need to interlinking resources.
I'm talking of using instance information and matching distances to create owl:sameAs interlinking. For example, geo:lat, geo:long can be used in order to match (e.g. using haversine distance) with other geolocated instances, or string matching measures like Jaro-Winkler could be applied for rdfs:label or any other string label. Some useful references: Volz, Julius, et al. Discovering and maintaining links on the web of data. Springer Berlin Heidelberg, 2009. Kalpa Gunaratna, Sarasi Lalithsena andAmit Sheth. Alignment and dataset identification of linked data in Semantic Web. DOI: 10.1002/widm.1121 Szekely, Pedro, et al. "Connecting the Smithsonian American Art Museum to the Linked Data Cloud." The Semantic Web: Semantics and Big Data. Springer Berlin Heidelberg, 2013. 593-607. Hope this helps Feel free to contact me Antonino > Hi Dimitris and Antonino, > > A couple of questions: > > When you mentioned interlinking methods, are you talking about instances > matching or schema matching? I am very interested in methods for instances > deduplication in a triplestore. Any reference? > > How do you keep a version control of the ontology changes with WebProtege? > Does it work fine with many contributors editing the ontology > simultaneously? How does DBPedia ontology evolved over time? These are all > relevant questions for other community-driven ontologies like VIVO ( > http://vivoweb.org). > > Best, > > Alexandre Rademaker > http://arademaker.github.com/ >