Chasing Streams with Existential Rules
This work addresses a gap in stream reasoning for rapidly changing data, but it is incremental as it builds on existing static database methods.
The paper tackles the problem of query answering over data streams using existential rules, extending the LARS framework to support these rules and ensuring decidability through temporal acyclicity notions.
We study reasoning with existential rules to perform query answering over streams of data. On static databases, this problem has been widely studied, but its extension to rapidly changing data has not yet been considered. To bridge this gap, we extend LARS, a well-known framework for rule-based stream reasoning, to support existential rules. For that, we show how to translate LARS with existentials into a semantics-preserving set of existential rules. As query answering with such rules is undecidable in general, we describe how to leverage the temporal nature of streams and present suitable notions of acyclicity that ensure decidability.