  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 on expressive logics that can be applied to
this setting, and point to further research directions in this area.

Logic in Computer Science;Artificial Intelligence