Work place: Centre de Recherche en Géomatique, Université Laval, Québec, Canada G1V 0A6
E-mail: thierry.badard@ulaval.ca
Website:
Research Interests: Data Structures and Algorithms, Data Compression, Database Management System
Biography
Thierry Badard, PhD., Eng. is professor in geoinformatics at the Department of geomatics sciences of Université Laval in Quebec City (Canada).
He is the director of the Centre for Research in Geomatics (CRG) and is also on the steering committee of the Big Data Research Centre (BDRC) at Université Laval. He has more than 20 years of experience and he has been involved and has led national and international R&D projects of importance. His research interest deals with geospatial Big data, location analytics, data integration and fusion for better decision support, geospatial Business Intelligence, IoT and smart cities. He acts as a chair, editor and reviewer for numerous international journals and scientific conferences and has already an important record of scientific contributions. Dr. Thierry Badard is also actively involved in the geospatial free and open source community. He is developer, administrator and project coordinator of several open source projects : GeoKettle, GeoMondrian, SOLAPLayers and GeOxygene. He is an OSGeo charter member and has acted as a member of the OSGeo conference committee and a reviewer for the OSGeo Journal for several years. He is one of the founding co-chairs the OSGeo Quebec local chapter and a founding co-chair of the ICA (International Cartographic Association) commission on open source geospatial technologies.
He has also recently founded Ekumen, a company specialised in Location analytics & geomarketing where he acts as CTO. For further details, please visit http://www.ekumen.biz & http://www.crg.ulaval.ca.
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.
[...] Read more.Subscribe to receive issue release notifications and newsletters from MECS Press journals