Stream reasoning: A survey and further research directions

Abstract

Data streams occur widely in various real world applications. The research on streaming data mainly focuses on the data management, query evaluation and optimization on these data, however the work on reasoning procedures for streaming knowledge bases on both the assertional and terminological levels is very limited. Typically reasoning services on large knowledge bases are very expensive, and need to be applied continuously when the data is received as a stream. Hence new techniques for optimizing this continuous process is needed for developing efficient reasoners on streaming data. In this paper, we survey the related research on reasoning that can be applied to this setting, summarize existing approaches according to a set of parameters, and point to further research directions in this area. © 2009 Springer-Verlag Berlin Heidelberg.