Keywords: Relational data, Ontologies, Ontologies catalog, Ontologies analysis and transformation, Relational learning
TL;DR: A Gateway to Relational Data Analysis and Transformation
Abstract: One of the major barriers to the training of statistical models on knowledge representations is the difficulty that scientists have in finding the best input data to be used for addressing their prediction goal. In addition to this, a key challenge is to determine how to manipulate these relational data, which are often in the form of particular triples (i.e., subject, predicate, object), to enable the learning process. This paper describes the LiveSchema initiative, namely a gateway that leverages the gold-mine of relational data collected by many existing ontology catalogs. By implementing a continuously updating aggregation facility, LiveSchema aims at providing a family of services that can be used to easily access, accurately analyze, transform and re-use data in a machine learning scenario.