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It is recognized that 80% of data have a spatial component (ex. street address, place name, geographic coordinates, map coordinates). Having the possibilities to display data on maps, to compare maps of different phenomena or epochs, and to combine maps with tables and statistical charts allows one to get more insights into spatial datasets. Furthermore,(More)
To exploit the full potential of the spatial and temporal dimensions of a data warehouse, new tools are needed. It has been shown that OLAP possesses a certain potential to support spatio-temporal analysis. However, without a spatial interface for viewing and manipulating the geometric component of the spatial data, the analysis may be incomplete. A new(More)
To support their analytical processes, today's organizations deploy data warehouses and client tools such as OLAP (On-Line Analytical Processing) to access, visualize, and analyze their integrated, aggregated and summarized data. Since a large part of these data have a spatial component, better client tools are required to take full advantage of the(More)
This paper presents a new category of decision-support tools that builds on today's Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP) technologies to facilitate Geographic Knowledge Discovery (GKD). This new category, named Spatial OLAP (SOLAP), has been an R&D topic for about 5 years in a few university labs and is now being(More)
BACKGROUND After its first detection in North America in New York in 1999, West Nile virus was detected for the first time in 2002 in the province of Quebec, Canada. This situation forced the Government of Quebec to adopt a public health protection plan against the virus. The plan comprises several fields of intervention including the monitoring of human(More)
It is well known that transactional and analysis systems each require a different database structure. In general, the database structure of transactional systems is optimized for consistency and efficient updates while the database structure of analysis systems is optimized for complex query performance. Non-spatial data are reorganized in data warehouses(More)
D'importants efforts sont déployés depuis une quinzaine d'années pour mettre en place des systèmes d'aide à la décision sur le territoire. Ces systèmes reposent toutefois sur les systèmes d'information géographique (SIG) et les approches transactionnelles habituelles (OLTP) pour produire l'information géodécisionnelle, souvent avec des délais inacceptables,(More)
BACKGROUND Every year, many deaths or health problems are directly linked to heat waves. Consequently, numerous jurisdictions around the world have developed intervention plans that are employed during extreme heat events; beyond their emergency sections, these plans generally include preventive measures to be implemented each year. Over the last five(More)
Spatial datacubes extend the datacube concept underlying the field of Business Intelligence (BI) into the realm of spatial analysis, geographic knowledge discovery, and spatial decision-support. The traditional computer science community has defined spatial datacubes and their fundamental components (e.g., spatial dimension and spatial measure) through(More)