ABSTAT: Linked Data Summaries with ABstraction and STATistics
Matteo Palmonari, Anisa Rula, Riccardo Porrini, Andrea Maurino, Blerina Spahiu, Vincenzo Ferme · Lecture notes in computer science · 2015
While much work has focused on continuously publishing Linked Open Data, little work considers how to help consumers to better understand existing datasets. ABSTAT framework aims at providing a better understanding of big and complex datasets by extracting summaries of linked data sets based on an ontology-driven data abstraction model. Our ABSTAT framework takes as input a data set and an ontology and returns an ontology-driven data summary as output. The summary is exported into RDF and then made accessible through a SPARQL endpoint and a web interface to support the navigation. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.