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Rule-based temporal query languages provide the expressive power andflexibility required to capture in a natural way complex analysis tasks overstreaming data. Stream processing applications, however, typically require nearreal-time response using limited resources. In particular, it becomes essentialthat the underpinning query language has favourable computational propertiesand that stream processing algorithms are able to keep only a small number ofpreviously received facts in memory at any point in time without sacrificingcorrectness. In this paper, we propose a recursive fragment of temporal Datalogwith tractable data complexity and study the properties of a generic streamreasoning algorithm for this fragment. We focus on the window validity problemas a way to minimise the number of time points for which the stream reasoningalgorithm needs to keep data in memory at any point in time.

The Window Validity Problem in Rule-Based Stream Reasoning