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Found 9 result(s)
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The Canada Open Data Project provides Government of Canada data to the public as potential driver for economic innovation. Searchable and browsable raw data is available for download, and the public can recommend specific data be made available.
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An open data sharing platform resulting from collaboration between cities and the Government of Quebec.
The range of CIRAD's research has given rise to numerous datasets and databases associating various types of data: primary (collected), secondary (analysed, aggregated, used for scientific articles, etc), qualitative and quantitative. These "collections" of research data are used for comparisons, to study processes and analyse change. They include: genetics and genomics data, data generated by trials and measurements (using laboratory instruments), data generated by modelling (interpolations, predictive models), long-term observation data (remote sensing, observatories, etc), data from surveys, cohorts, interviews with players.
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The National Air Pollution Surveillance (NAPS) Program provides accurate and long-term air quality data of a uniform standard across Canada. The NAPS Network has a Canada-Wide database of criteria air contaminants from the early 1970s to the present for designated NAPS sites, as well as provincial, territorial and other sites. Trace contaminants are also monitored at several stations in the network and analyzed by the laboratory at River Road.
Country
The Canadian Longitudinal Study on Aging (CLSA) is a large, national, long-term study of more than 50,000 individuals who were between the ages of 45 and 85 when recruited. These participants will be followed until 2033 or death. The aim of the CLSA is to find ways to help us live long and live well, and understand why some people age in healthy fashion while others do not.
Knoema is a knowledge platform. The basic idea is to connect data with analytical and presentation tools. As a result, we end with one uniformed platform for users to access, present and share data-driven content. Within Knoema, we capture most aspects of a typical data use cycle: accessing data from multiple sources, bringing relevant indicators into a common space, visualizing figures, applying analytical functions, creating a set of dashboards, and presenting the outcome.