Understanding spatial data and how to design visualizations is becoming easier for non-specialists with the latest mapping software. This is exciting - almost everyone who works with data will encounter situations when mapping it is critical to understanding trends, making sense of complexity, or pinpointing locations. But skills alone are often not enough, it’s the whole workflow that matters. This summer we are creating a robust curriculum to teach mapping skills with the whole workflow in mind.
We will be using this curriculum in two upcoming workshops we are leading for the New Organizing Institute (NOI), part of their upcoming Advanced Data trainings happening in Berkeley, CA July 24 to 30 and in Washington, DC August 21 - 27. (Last we heard there were a few spaces left. If you’re interested, contact Josh Wolf at [email protected])
The workshops will walk through in detail how to use TileMill to design and share custom maps, but will begin by covering GIS basics, tools for processing data like QuantumGIS, and tools for working with tabular data like Google Refine. We hope that people will leave with not only a good understanding on how to make beautiful custom maps, but also how to clean up and best utilize their data.
Here is a quick look at training curriculum. We’ll be posting parts of this to support.mapbox.com as we further develop it, along with other articles that sketch out the workflows for mapping that we find most powerful.
If you’re interested in a training like this not tailored to organizers, please contact us at [email protected] for more information.
The workshop runs three hours and is broken into three sections, each divided in half by a lecture and a guided hands on walk through.
Hour 1: Maps
- The power of maps: trends, storytelling, data exploration (examples, case studies)
- Landscape of software tools for working with spatial data: ArcGIS, Google Earth, QGIS, TileMill (10 min)
- Hands on: Using TileMill to design a map with scale points (radius by data value)
Hour 2: Data
- Basics of longitude, latitude, projections
- Common geodata formats: Shapefile, KML, GeoJSON, PostGIS
- Where to find data and what to expect, gochas you will hit
- Hands on: Create a GeoJSON file in a text editor and convert to a shapefile and KML in QGIS, open in TileMill and Google Earth.
Hour 3: Analysis and Exploration
- Techniques for manipulating and analyzing data
- Tools for querying, filtering, and aggregation: QGIS, SQLite, PostGIS
- Hands on: Working with Census data: filtering in QGIS, styling in TileMIll