ALASKA for Ontology Based Data Access
Choosing the tools for the management of large and semi-structured knowledge bases has always been considered as a quite crafty task. This is due to the emergence of different solutions in a short period of time, and also to the lack of benchmarking available solutions. In this paper, we use ALASKA, a logical framework, that enables the comparison of different storage solutions at the same logical level. ALASKA translates different data representation languages such as relational databases, graph structures or RDF triples into logics. We use the platform to load semi-structured knowledge bases, store, and perform conjunctive queries over relational and non-relational storage systems.
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