Some Thoughts on Civic Indexes | MIT Center for Civic Media
Rahul Bhargava is a researcher and technologist specializing in civic technology and data literacy. He creates interactive websites used by hundreds of thousands, playful educational experiences across the globe, and award-winning visualizations for museum settings. As a Research Scientist at the MIT Center for Civic Media, Rahul leads technical development on projects ranging from interfaces for quantitative news analysis, to platforms for crowd-sourced sensing. He has a special interest in how new technologies are introduced to people in settings focused on learning. Rahul is a drummer and father based in Somerville, MA.
Some Thoughts on Civic Indexes
Parks are awesome, but does your city have enough of them? The Trust for Public Land’s ParkScore(tm) tries to asses this with a simple score out of 100. I’m seeing this kind of “civic index” more and more often. The biggest example I see if WalkScore, which has become omnipresent on real estate websites (much to my pleasure). Both are civic indexes that serve as proxies for complicated algorithms, but while TPL is definitely talking to planners, WalkScore is talking directly to regular folks.
So what is the role of these civic indexes? If you really care about parks, sharing your community’s ParkScore with your local planning office could help motivate energy around building parks in underserved parts of town. My local WalkScore certainly played a role in me purchasing my house. These indexes reframe the conversation into the home turf of the advocacy group. Once you start talking about ParkScore you’ve implicitly accepted their definition of an ideal park distribution. Same with WalkScore - they’re explicitly advocating for more walkable communities. Both can serve as an advocacy tool - highlighting underserved areas. Both sites publish much of their methodology (though TPL has more details than WalkScore).
Are there other high-level “civic indexes” you’ve seen around? Do these simplify the conversation too much, or are they a valuable advocacy tool?
PS: Since TPL only scored the top 40 cities, I wanted to compute my own town’s ParkScore. I reproduced their algorithm in a simple ruby library, but of course the hard part is gathering the appropriate data. I contacted the city, but I’m still working on it...