Pervasive computing devices are able to generate enormous amounts of distributed data, from which knowledge about situations and facts occurring in the world should be inferred for the use of pervasive services. However accessing and managing effectively such a huge amount of distributed information is challenging for services. In this paper after having outlined these challenges, we propose a self-organized agent-based approach to autonomously organize distributed contextual data items into sorts of knowledge networks. Knowledge networks are conceived as an alive self-organized layer in charge of managing data, that can facilitate services in extracting useful information out of a large amount of distributed items. In particular, we present the W4 Data Model we used to represent data and the self-organized approach to build Knowledge Networks. Some experimental results are reported to support our arguments and proposal, and related research work are extensively discussed. © 2010 Springer-Verlag Berlin Heidelberg.
Contextual data management and retrieval: A self-organized approach / Castelli, G.; Zambonelli, F.. - 324:(2010), pp. 145-162. [10.1007/978-3-642-16089-9_9]