Community Indicators for Your Community

Real, lasting community change is built around knowing where you are, where you want to be, and whether your efforts are making a difference. Indicators are a necessary ingredient for sustainable change. And the process of selecting community indicators -- who chooses, how they choose, what they choose -- is as important as the data you select.

The Jacksonville Community Council (JCCI) understands indicators and community change, with more than 25 years of producing the annual Quality of Life Progress Report for Jacksonville and the Northeast Florida region, and two decades of helping other communities develop their own sustainable indicators projects. JCCI consultants give you the information you need to measure progress, identify priorities for action, and assess results.

I'd like to talk with you personally about how we can help. E-mail me at
ben@jcci.org, call (904) 396-3052, or visit CommunityWorks for more information. From San Antonio to Siberia, we're ready and willing to assist.


Thursday, July 31, 2008

Five Types of Data Visualization People

Flowing Data presents an interesting set of categories of people who are interested in data visualization. The list includes these five types:

  • The Technician, focused on implementation (how the hardware/software support the visualization);
  • The Analyzer, focused on the data (what are the numbers and what do they say?);
  • The Artist, focused on the visuals (is it pretty?);
  • The Outsider, focused on context (what's the other information we need to understand the data?); and
  • The Light Bulb, focused on the picture -- the one with the Big Idea that everyone else has to sweat to implement.

Tasty Data Goodies, the blog from Swivel, talks about the five categories, and includes a graph purporting to show the relative size of the five types. Except the graph is based on a sample size of 10. And people could choose more than one category. I'm not reproducing the graph (you can see it here if you really want to), but why did they? I thought they knew data better than that. Just because you have some numbers doesn't mean you have information.

Back to the five categories. Do you see yourself in them? Your project partners (staff or volunteers)? Are these categorizations complete? Are they useful?

(As a side note, the Flowing Data blog is pretty neat -- I'm adding it to the blogroll on this page. If you have other suggestions for blogs that we should be linking to, please drop me a line.)


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