Abstract – Armelle Natacha Ndjafa
Towards large-scale distributed data querying using specialized and enriched dataspaces
Over the last years, information technologies have provided many data management capabilities that improve access and management of distributed heterogeneous data.
We will present a contribution towards a system for consistently querying this large amounts of information. The proposal is based on the dataspace paradigm. To this end, we extend an existing dataspace data model and the corresponding dataspace query language. This enables us to define the concept of specialized dataspaces, which integrate data items resulting from a query defined in the query language mentioned above processed over the set of distributed data sources. Moreover, we propose a method to semantically enrich the specialized dataspaces by discovering semantic relations using external ontologies, thus increasing the degree of data integration and the query processing performance.