ART Lab infrastructure for semantic Big Data processing

摘要

In this paper we briefly describe the ART Lab infrastructure for semantic Big Bata processing. Our most relevant contribution is the definition of an architecture supporting ontology development driven by knowledge acquired from heterogeneous resources, such as documents and web pages. The overall perspective is to propose a gluing architecture driving and supporting the entire flow of information, from data acquisition from external heterogeneous resources to their exploitation for RDF triplification. In such an architecture, the unstructured content analysis capabilities of frameworks such as UIMA are integrated in a coordinated environment supporting the processing, transformation and projection of produced metadata into RDF semantic repositories, which are managed by Semantic Turkey, our platform for Knowledge Acquisition and Management. Further contributions relate to the possibility of easily managing high dimension repositories (e.g., thesauri, vocabularies, etc.), and supporting end users for sharing the “logics” under the reasoning processes!