Last week we held another bootcamp on Spatial Data Science. We had three packed days learning about the concepts, tools and workflow associated with spatial databases, analysis and visualizations. Our goal was not to teach a specific suite of tools but rather to teach participants how to develop and refine repeatable and testable workflows for spatial data using common standard programming practices.
On Day 1 we focused on setting up a collaborative virtual data environment through virtual machines, spatial databases (PostgreSQL/PostGIS) with multi-user editing and versioning (GeoGig). We also talked about open data and open standards, and moderndata formats and tools (GeoJSON, GDAL). On Day 2 we focused on open analytical tools for spatial data. We focused on Python (i.e. PySAL, NumPy, PyCharm, iPython Notebook), and R tools. Day 3 was dedicated to the web stack, and visualization via ESRI Online, CartoDB, and Leaflet. Web mapping is great, and as OpenGeo.org says: “Internet maps appear magical: portals into infinitely large, infinitely deep pools of data. But they aren't magical, they are built of a few standard pieces of technology, and the pieces can be re-arranged and sourced from different places.…Anyone can build an internet map."
All-in-all it was a great time spent with a collection of very interesting mapping professionals from around the country. Thanks to everyone!/span>