Pervasive and mobile computing has peculiarities -such as highly volatile connectivity, unexpected disconnections, location-dependency, reduced energy, storage and computational availability among others- making them different from traditional wired and dependable computing paradigms. Research challenges are thus posed and novel techniques are required in order to leverage resource discovery, matchmaking and reasoning for efficient and reliable applications and services in wireless environments.

It could be useful that large amount of disseminated data, annotated in a given machine understandable format (such as RDF, OWL), stored in RFID tags or cluster head sensors or even PDAs and mobile devices, are properly recomposed to enable semantic-based reasoning on a consistent and self-contained part of a given domain. In particular, effective methods for selecting on-the-fly suitable portions of knowledge available in a given context for drawing conclusions from a set of given facts are strongly required. Opportunistic data integration enables pieces of knowledge (coming from several autonomous and decentralized data sources) to be properly combined in order to (re)build a proper fragment of the knowledge available in a mobile ad-hoc scenario. In this way, inapplicable centralized knowledge bases, not-realistic in mobile and resource-constrained contexts could be avoided.

This paradigm is borrowed from the Semantic Web vision and adapting it to the Internet of Things as resulting from the integration and collaboration of a plethora of small entities each one providing and requiring a portion of knowledge and reasoning capabilities. According to this assumption, Semantic-based Opportunistic Data Management requires advanced and flexible information management models suitable for coping with unpredictability, decentralization and resource scarcity featuring ubiquitous computing.

The first edition of the International Workshop on “Semantic-based Opportunistic Data Management'' (SODM) will discuss about data management issues related to the Internet of Things and the relationships with other Semantic Web technologies, proposing new models, languages and applications.