Emergent communities for semantic collaboration in multi-knowledge environments : methods and techniques

The need of methods and techniques to foster semantic collaboration is a challenging issue at the current stage of development of P2P networks and open distributed systems in general. In this respect, the emergence of collaboration among peers requires the capabilities to share data and resources by dynamically selecting the most appropriate partners within the context of a given task. These scenarios are multi-knowledge, in that no centralized authorities are defined to manage a comprehensive view of the resources shared by all the nodes in the system, due to the high dynamism and variability of collaboration and sharing requirements. With respect to this scenario, the thesis work has focused on investigating the peculiar aspects and requirements of knowledge sharing in open distributed systems, and in P2P systems in particular. In this context, ontologies and ontology matching techniques have been identified as a key solution for enabling peers with similar contents to gradually “emerge” and for allowing the network to self-configure by linking them as semantic neighbors. The main contribution of the thesis work regards the definition of methods and techniques for enforcing semantic collaboration among autonomously emergent semantic neighbors. In particular, two main goals have been obtained. On one side, the development of a matching-driven semantic routing mechanism, called H-Link, for scalable distribution of knowledge requests on a semantic basis and for effective sharing of distributed resources. On the other side, the defi- nition of consensus-driven techniques which exploit ontological resource descriptions and ontology matching in order to form, maintain, and disband semantic communities of peers, with application to the Helios knowledge-sharing P2P system.