Abstract
We propose a novel framework for ontology-based access to temporal log data using a datalog
extension datalogMTL of the Horn fragment of the metric temporal logic MTL. We show
that datalogMTL is EXPSPACE-complete even with punctual intervals, in which case full MTL is
known to be undecidable. We also prove that nonrecursive datalogMTL is PSPACE-complete for
combined complexity and in AC0 for data complexity.We demonstrate by two real-world use cases
that nonrecursive datalogMTL programs can express complex temporal concepts from typical user
queries and thereby facilitate access to temporal log data. Our experiments with Siemens turbine
data and MesoWest weather data show that datalogMTL ontology-mediated queries are efficient
and scale on large datasets.