text: The rise of smart applications has drawn interest to logical reasoning over data streams. Recently, different query languages and stream processing reasoning engines were proposed in different communities. However, due to a lack of theoretical foundations, the expressivity and semantics of these diverse approaches are given only informally. Towards clear specifications and means for analytic study, a formal framework is needed to define their semantics in precise terms. To this end, we present a first step towards an ideal semantics that allows for exact descriptions and comparisons of stream reasoning systems.
  @cite_11: Data Stream Management Systems (DSMS) have attracted much interest from the database community, and extensions of relational database languages were proposed for expressing continuous queries on data streams. However, while relational databases were built on the solid bedrock of logic, the same cannot be said for DSMS. Thus, a logic-based reconstruction of DSMS languages and their unique computational model is long overdue. Indeed, the banning of blocking queries and the fact that stream data are ordered by their arrival timestamps represent major new aspects that have yet to be characterized by simple theories. In this paper, we show that these new requirements can be modeled using the familiar deductive database concepts of closed-world assumption and explicit local stratification. Besides its obvious theoretical interest, this approach leads to the design of a powerful version of Datalog for data streams. This language is called Streamlog and takes the query and application languages of DSMS to new levels of expressive power, by removing the unnecessary limitations that severely impair current commercial systems and research prototypes.
summary: StreamLog Another logic-based approach towards stream reasoning is StreamLog @cite_11 . It makes use of Datalog and introduces whose first arguments are timestamps. By introducing which have syntactical restrictions on temporal rules, StreamLog defines (for which Closed World Assumption can be safely applied) that can be used in recursive rules in a stream setting. Since sequential programs are locally stratified, they have efficiently computable perfect (i.e., unique) models. Similar to capturing a fragment of Reactive ASP, we can capture StreamLog by converting temporal atoms @math to expressions @math and employing safety conditions to rules to simulate non-blocking negation. Moreover, we plan for having weaker notions of negation that might block rules but just for a bounded number of time points to the future.