Towards Effective ASP-based Stream Reasoning: Facilitate the Reasoning over Patterns of Events
Luca Laboccetta, Elena Mastria, Francesco Calimeri, Nicola Leone, Simona Perri, Giorgio Terracina · 2024
In the latest years, Stream Reasoning (SR) has become increasingly relevant in various scenarios where it is required to reason over heterogeneous and highly dynamic data streams, typically along with large background knowledge bases, such as Smart Cities, IoT, Healthcare, etc. In this context, several solutions based on Answer Set Programming (ASP) have been successfully employed. Nevertheless, real applications showed that it is often needed to deal with events over the timeline generating specific patterns that, in turn, can fire additional events or invalidate others. In this respect, current ASP-based state of the art systems appear not fully satisfactory, both from a modelling point of view and when it comes to usability and performance. In this work, starting from a well-established ASP-based SR solution, namely I-DLV-sr, we: (i) extend the language with means to explicitly define, identify and reason about patterns of events and their consequences, possibly spanning across the timeline; (ii) generalize the system architecture so that it is able to decouple language and implementation support from the choice of a specific ASP system, thus allowing the user to select the one best suited to the specific SR scenario at hand. The result is DP-sr: a purely Declarative Programming framework for Stream Reasoning. DP-sr is put to the test, showing both the ease in modelling and performance improvements.