Ruben Verborgh’s data

Matches in Ruben’s data for { ?s ?p "Handling Big Data is often hampered by integration challenges, especially when speed, efficiency and accuracy are critical. In Semantic Web, integration is achieved by aligning multiple representations of the same entities, appearing within distributed heterogeneous sources and by annotating data using same vocabularies. However, mapping different sources to RDF separately, generating multiple URIs for distinct instances of same entities, hampers advanced and automated data fusion and prevents benefiting from data semantic representation. We introduce a unified knowledge framework, created already at mapping level, to enable a successful business ecosystem built on top of enriched and combined datasets, proving that the integration of data from multiple heterogeneous sources, produces added value."@en }

• publication abstract "Handling Big Data is often hampered by integration challenges, especially when speed, efficiency and accuracy are critical. In Semantic Web, integration is achieved by aligning multiple representations of the same entities, appearing within distributed heterogeneous sources and by annotating data using same vocabularies. However, mapping different sources to RDF separately, generating multiple URIs for distinct instances of same entities, hampers advanced and automated data fusion and prevents benefiting from data semantic representation. We introduce a unified knowledge framework, created already at mapping level, to enable a successful business ecosystem built on top of enriched and combined datasets, proving that the integration of data from multiple heterogeneous sources, produces added value.".