Introduction to the Special Issue: Semantic Matchmaking and Resource Retrieval on the Web

The promise of the Semantic Web is to make machine understandable all the information available on the Web. The knowledge on any specific domain can be stored in an explicit and reusable format by means of ontology languages. Moreover, exploiting the formal semantics of ontology languages, implicit knowledge can be elicited through automated reasoning mechanisms. Semantic Web technologies open new scenarios and suggest new approaches to classical problems. The envisaged applications are obvious in e-commerce, Web services, and peer-to-peer interaction, to mention a few. The formalization of machine-understandable annotations facilitates interoperability among heterogeneous resources, while avoiding usual drawbacks of unstructured data. Having an explicit semantics associated to queries and resource descriptions inherently allows a mechanized system to perform matchmaking and, subsequently, retrieval—based on the meaning of “what the resource is”—that is smarter than (whatever enhanced version of) pure text matching. We all know that the Web is an “open environment.” However, this is true not only for the technological infrastructure, but also for the information content. New information is continuously added to already existing resources, and old data are deleted. We may never own all the knowledge related to a resource; there can always be some pieces of missing, under-specified, information. Using classical data models like the ones behind modern databases, it is not possible to deal with such characteristics of an informational open environment. As a matter of fact, the huge research effort devoted to semi-structured data witnesses the existence of this problem from the point of view of database researchers. Unfortunately, databases always assume a closure of the data when answering queries. Semantic Web technologies are able to cope with informational openness by adopting the so-called open-world assumption (OWA). In other words, the system assumes that missing information can always be filled later on if needed, which is to say, a Semantic Web system does not treat the absence of a datum as evidence of absence and can distinguish it from negative information. Regardless of the intuitive advantages introduced by Semantic Web, its expansion is still far from being a fact. There are several reasons for this situation: