The AISA KG introduced with Deliverable D4.1 is a RDF dataset holding all the static and dynamic data and metadata relevant for AI situational awareness. The AISA KG is stored on a KG server and queried and updated via SPARQL. The KG schema is specified in RDF Schema and SHACL. Data and metadata are added dynamically to the KG and processed and queried via application-specific engines mainly implemented in Java. A central control component implemented in Java is responsible for recurring invocation of the different engines. Advanced reasoning tasks over the KG are to be realized based on rule-based knowledge represented in Prolog.
The design problem tackled by Task 4.2 is to improve accessing the KG from Prolog by designing a KGProlog mapper that takes care of data interchange and mapping between Prolog engine and KG, so that Prolog programmers can easily develop Prolog programs, which read from and write to the KG. We investigate schema-oblivious and schema-aware KG-Prolog mapping. The schema-oblivious approach can be realized easily but is unwieldy for Prolog programmers when it comes to reading complex KG data. Schema-aware KG-Prolog mapping provides the contents of the KG in a form amenable to Prolog programmers according to the KG schema. We implement the schema-aware approach in three different variants and conduct preliminary performance studies for comparison. We provide a full integration of Prolog engine and AISA KG system for the schema-oblivious approach together with one variant of the schema-aware approach.
This deliverable is part of a project that has received funding from the SESAR Joint Undertaking under grant agreement No 892618 under European Union?s Horizon 2020 research and innovation programme.