Michal Migurski's notebook, listening post, and soapbox. Subscribe to this blog. Check out the rest of my site as well.

Jan 9, 2012 5:27am

take my class at gaffta next month

I’ll be teaching a four-day class at the Gray Area Foundation For The Arts next month, Visualizing and Mapping Data. It’ll be a four-parter, Tuesday and Thursday evenings at GAFFTA’s San Francisco space. I’ll be covering mapping from both a browser and server perspective, focusing the presentation of data.

Go sign up!

Here’s an early draft of my class notes; these will change but not substantially:

This four-day workshop will follow the lifecycle of data, from its raw collection to preparation and presentation for the web. We’ll explore where geographic data originates, how it’s transformed to work online, how to see it flow and move, and finally how to publish a view into that data to the web with simple browser-based tools. We’ll work with data from Twitter and OpenStreetMap, push it through filters and viewers, and publish it to the open web.

This class will cover both browser-side Javascript code and server-side Python code.

Week One: Foregrounds

Meeting 1: Getting dots on maps

We’ll be working with street-level data for the duration of the class, so we’ll start here with some introductory concepts like interactive slippy maps and image tiles. We’ll take Google Maps apart into its component pieces to see how they work, add a selection of point-based data to a map, and finish up with a working example using freely-available Javascript mapping tools.

Meeting 2: Where data comes from

Data can come from all kinds of sources, and frequently it needs to be processed, cleaned, and prepared for use on the web. Become self-sufficient in making location data useful to others. We’ll look at local data sources like 311 calls, addresses, and demographic information and run them through a variety of tools to make them ready for online publishing.

Week Two: Backgrounds

Meeting 3: Choosing your own background

Commonly-available road maps designed for displaying driving directions or finding business addresses don’t always work in combination with arbitrary or complex data. We’ll look at alternate sources of street-level cartography and talk about the ways each might be appropriate to different data sets. We’ll finish up with a dive into the OpenStreetMap data set and the process of designing your own custom cartography.

Meeting 4: Spatial data

Dots on maps are just one of many ways to display data. Heat maps, for example, can be used to show characteristics of large areas of data such as zip codes or census tracts using color. We’ll look at ways to prepare heat map layers and integrate them with our other maps, and finish up with advanced topics like aerial photographs and raster data.

October 2021
Su M Tu W Th F Sa

Recent Entries

  1. Mapping Remote Roads with OpenStreetMap, RapiD, and QGIS
  2. How It’s Made: A PlanScore Predictive Model for Partisan Elections
  3. Micromobility Data Policies: A Survey of City Needs
  4. Open Precinct Data
  5. Scoring Pennsylvania
  6. Coming To A Street Near You: Help Remix Create a New Tool for Street Designers
  7. planscore: a project to score gerrymandered district plans
  8. blog all dog-eared pages: human transit
  9. the levity of serverlessness
  10. three open data projects: openstreetmap, openaddresses, and who’s on first
  11. building up redistricting data for North Carolina
  12. district plans by the hundredweight
  13. baby steps towards measuring the efficiency gap
  14. things I’ve recently learned about legislative redistricting
  15. oh no
  16. landsat satellite imagery is easy to use
  17. openstreetmap: robots, crisis, and craft mappers
  18. quoted in the news
  19. dockering address data
  20. blog all dog-eared pages: the best and the brightest