Towards the Integration of Knowledge Organization Systems with the Linked Data Cloud

In representing the shared view of all the people involved, building a Knowledge Organization System (KOS) from scratch is extremely costly, and it is therefore fundamental to reuse existing resources. This can be done by progressively extending the KOS with knowledge coming from similar KOS and by promoting interoperability among them. The linked data initiative is indeed fostering people to share and integrate their datasets into a giant network of interconnected resources. This enables different applications to interoperate and share their data. However, the integration should take into account the purpose of the datasets and make explicit the semantics. In fact, the difference in the purpose is reflected in the difference in the semantics. With this paper we (a) highlight the potential problems that may arise by not taking into account purpose and semantics, (b) make clear how the difference in the purpose is reflected in totally different semantics and (c) provide an algorithm to translate from one semantic into another as a preliminary step towards the integration of ontologies designed for different purposes. This will allow reusing the ontologies even in contexts different from those in which they were designed.