An Extension of DIG 2.0 for Handling Bulk Data

The research community has noted the need to retrieve the instance level of an ontology from bulk data stored in external data sources (e.g., a relational database), in order to delegate to the external source all aspects of the actual management of the data. To achieve this, several methodologies have been recently developed to represent and reason about what we call here Ontologies with Linking Axioms. However, existing DL reasoners cannot properly deal with such ontologies. Indeed, including the instance level in the communication with a DL reasoner can cause a heavy communication overhead, and goes against the requirement of delegating data management to the external source. To overcome these problems, we present here an extension to the DIG 2.0 Interface that allows for the specification and management of Ontologies with Linking Axioms. The extension is a general framework which can accommodate any type of data source and linking axiom through specific implementations. We also p...

• Type: Conference
• Year: 2007
• Where: OWLED
• Authors: Diego Calvanese, Mariano Rodriguez-Muro
• Keywords: Data Sources, Dl Reasoner, Instance Level, Natural Language Processing, OWLED 2007