Projects description

ACE : Aristotelian Class Explorer : classification and relations between concepts. Classification of instances and relations between concepts/instances of mining and geological data. The model describes how composition and spatio-temporal relations structure the representation of mining and geological data. The mining and geological data include : mineral deposit information, spatial information, geographical information and technical characteristics. In the project the characterization of these representations are introduced formally then the Aristotelian method of classification is used. In collaboration with : Pr David Poole UBC, Clinton Smyth GeoreferenceOnline.

BIOSTAND : Standardized protocol for Biodiversity monitoring at local and global-scale. In collaboration with Dr Eric Coissac Laboratoire d’Ecologie Alpine LECA.

COIN : The Coordinated Online Information Network (COIN) is a geospatial-based program with semantic search capacity for support of Yukon’s natural resource licensing and allocation procedures. COIN is funded by Natural Resources Canada NRCan. COIN is designed to provide a seamless technical means for all parties interested in the adjudication of Yukon’s natural resources to readily access and assess relevant information regarding resource-related projects (e.g. energy, mining, etc…) within specific geographic regions. The lead project proponent for COIN is the Yukon Water Board (YWB) and will be conducted in cooperation with the Yukon Government Energy Mines and Resources (EMR). Technical support for the initiative will be supported and coordinated locally by Dr. Chad P. Gubala (technical consultant to the YWB and EMR), with collaborators from the University of Alberta Pr Rick Chalaturnyk and the Université de Grenoble Laboratoire d’Informatique LIG-STeamer.

MAP-EON : Modeling and Analytic tools for Publishing Environmental Observatory iNformation : development of advanced, knowledge-based tools to understand the evolution of the environmental impacts of climate change and other anthropogenic effects upon sensitive ecosystems. MAP-EON proposes to share and publish environmental data through the development and application of a semantic-based network system for the presentation and integration of environmental effects data and information. This approach is a web-based multi domain knowledge and inter-operable exchange network. In collaboration with Dr Marianne S.V Douglas, Queen’s University.