Triplifying equivalence set graphs

In order to conduct large-scale semantic analyses, it is necessary to calculate the deductive closure of very large hierarchical structures. Unfortunately, contemporary reasoners cannot be applied at this scale, unless they rely on expensive hardware such as a multi-node in-memory cluster. In order to handle large-scale semantic analyses on commodity hardware such as regular laptops we introduced [1] a novel data structure called Equivalence Set Graph (ESG). An ESG allows to specify compact views of large RDF graphs thus easing the accomplishment of statistical observations like the number of concepts defined in a graph, the shape of ontological hierarchies etc. ESGs are built by a procedure presented in [1] that delivers graphs as a set of maps storing nodes and edges. In this demo paper (i) we show how facts entailed by an ESG and the graph itself can be specified in RDF following a novel introduced ontology; and, (ii) we present two datasets resulting from the triplification of two ESG graphs (one for classes and one for properties).