Such flexibility to navigate into space as well as time to analyze a phenomenon
requires a very efficient coupling between the GIS and the OLAP, in terms of interface,
functions, and speed. We have encountered such needs in different experiments
with university researchers (e.g., archaeologists, kinesiologists) and real-life
projects at the Quebec National Institute of Public Health (users = epidemiologists),
the Quebec Ministry of Transportation (users = civil engineers), Laval University
Spatial Online Analytical Processing (SOLAP) 0
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Executive Vice-Presidency (users = students recruitment team), Canada National
Coast Guard (users = incident analysts), and so forth.
Typically, most transactional and analytical applications are simple from a geomatics
point of view. They typically use spatial data obtained from a single source, they are
out-of-date (one or more years old is the rule), they are incomplete and they show
limited precision regarding the position of objects (in the order of tens of meters,
and more). Although this is sufficient for most users (e.g., tourists, news, routing),
other users have more complex needs that require frequent updates, integration of
data from different sources, integration of data from different epochs, integration of
field measurements, integration of real time data, and so on.
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