Carto is a cloud computing platform that provides GIS and web mapping tools for display in a web browser.
Based on the data acquired from Vancouver Open Data Catalog, the process of parse, filter and mine are accomplished using R which shadow the procedures documented in this case: the https://blogs.ubc.ca/pattieshang/vancouver-crimes-webmap-r-leaflet/
Then the geocoded and classified dataset was uploaded to Carto for representation. The illustration options are plenty! The Torque layer wizard breaks down the overall monthly data into data occurrences and flashes each cases right in front of your eyes as they occurs. It’s a novel way of illustrating the “happening” of events.
here’s the animated version:
p.s. the color of the legend may not be appearing in IE browser.
for a full view, please follow link: https://pattieshang.carto.com/viz/3c6d6a2a-a60b-11e6-8ccf-0e98b61680bf/public_map
If wanting to get a sense of which neighbouhood / area of Vancouver where a lot of the calls were made, a cluster map may be more instrumental in this case.
Cluster map layer type renders a cluster of points in close proximity of a given area.
(might need to zoom in to get a better view, alternatively: https://pattieshang.carto.com/viz/70302110-a613-11e6-9961-0e05a8b3e3d7/public_map)
It can be seen that bigger cluster of calls are made in Kitslano, downtown and Kensington-Cedar Cottage neighbourhoods.
Upon reflection, proper parsing, filtering, and mining of the data are essential to convey meaningful messages in the representation stages. Specifically for geospatial data, records should be geocoded, offset to avoid overlapping, properly categorized, and standardized in order to be illustrated effectively. If the data is handled well, exploring mapping options using an established Java Script Library can be a lot of fun!