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Frederic Hubert

Work place: Centre de Recherche en Géomatique, Université Laval, Québec, Canada G1V 0A6

E-mail: frederic.hubert@ulaval.ca

Website:

Research Interests: Materials Science

Biography

Frédéric Hubert, Ph.D., received his PhD degree in computer sciences in 2003 from University of Caen (France).
He has more than 18 years of experience in the Geoinformatics field. Since 2007, he is a professor at the Department of Geomatics Sciences at Université Laval, Québec, Canada. He is also member of the Centre de Recherche en Géomatique (CRG). His research interests are mainly concentrated on geovisualization, geospatial business intelligence, geospatial multimodal interactions, mobile spatial context, mobile augmented reality, and geospatial web services. Currently, he is more involved in research on cultural and noise mapping in urban and rural contexts. He has also been reviewer for various international scientific conferences and journals.
Dr Hubert is a member of different associations (ISPRS, ICA, CIG, OSGEO). He has published over 30 papers in peer-reviewed journals, conferences. He was also involved, as co-editor, in 3 books.

Author Articles
Towards Semantic Geo/BI: A Novel Approach for Semantically Enriching Geo/BI Data with OWL Ontological Layers (OOLAP and ODW) to Enable Semantic Exploration, Analysis and Discovery of Geospatial Business Intelligence Knowledge

By Belko Abdoul Aziz Diallo Thierry Badard Frederic Hubert Sylvie Daniel

DOI: https://doi.org/10.5815/ijieeb.2018.06.01, Pub. Date: 8 Nov. 2018

To contribute in filling up the semantic gap in data warehouses and OLAP data cubes, and enable semantic exploration and reasoning on them, this paper highlights the need for semantically augmenting Geo/BI data with convenient semantic relations, and provides OWL-based ontologies (ODW and OOLAP) which are capable of replicating data warehouses (respectively OLAP data cubes) in the form semantic data with respect of Geo/BI data structures, and which enable the possibility of augmenting these semantic BI data with semantic relations. Moreover, the paper demonstrates how ODW and OOLAP ontologies can be combined to current Geo/BI data structures to deliver either pure semantic Geo/BI data or mixed semantically interrelated Geo/BI data to business professionals.

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