Data warehousing and knowledge discovery from sensors and streams

Abstract

During last years, the issue of effectively and efficiently supporting data warehousing and knowledge discovery from sensor networks, and, more generally, data stream sources, which can be reasonably intended as a meaningfully generalization of the former kind of networks, is gaining a more and more a great deal of interest from the data warehousing and knowledge discovery research community. Main research issues in this scientific field arise from the clear and well-recognized unsuitability of traditional data warehousing and knowledge discovery methodologies, techniques and algorithms in dealing with the new challenges posed by sensor network data and, more generally, data streams. Indeed, traditional approaches are meant for multi-step methodologies and techniques, and multi-scan algorithms, which cannot be straightforwardly applied to sensor network data and data streams, due to wellknown limitations such as boundedmemory, online/timely data processing, need for one-pass techniques, energy consumption issues etc. Starting from these limitations, a plethora of data warehousing and knowledge discovery methodologies, techniques and algorithms have been proposed during these last years, and, simultaneously, a more and more large number of research events have focused their attention to this leading research challenge. Following this actual trend, the special issue on “Data Warehousing and Knowledge Discovery from Sensors and Streams” of Knowledge and Information Systems puts emphasis on both theoretical and practical aspects of data warehousing and knowledge discovery from sensor network data and data streams, from foundations to theory, and from methodologies to applications. With the aim of adequately fulfilling both theoretical and practical issues deriving from data warehousing and knowledge discovery from sensor network data and data streams, this special issue contains five papers,which have gone through two rigorous review rounds before being accepted for final inclusion. Some of the contributions of this special issue have been invited for submission as best papers from the First International Workshop on Data Warehousing and Knowledge Discovery from Sensors and Streams (DKSS 2009) held in Marina