Jan 212018
A Bit of a Rant on Data

Road sign that reads Dangerous Intersection AheadI’m a wee bit active on Twitter, where I find many resources, experts I can quickly question on a fine point of transportation policy or design, and inspiration. By now we all recognize the dark side as well — the ease and speed with which bad information spreads, particularly if it’s packaged with a catchy tagline or striking graphic. Hence this post on a thread I spun out about an infographic that is once again making the rounds.

I’ve always been a researcher at heart. When I served in the Idaho state legislature, I did homework before introducing any legislation so I could point to existing models and a firm foundation for the policy I proposed. I went to graduate school (MPA and coursework toward a PhD I didn’t finish) — more research, mostly in original sources. I worked at a research university campus for nearly 15 years, placing our faculty’s findings into appropriate context to communicate the value of their work. When I worked in bike advocacy I continued this approach; the information we provided to decision-makers was grounded in much more than our love of bicycling.

I’m now back in the public sector, responsible for communicating meaningful data on active transportation so we can address the safety, mobility, and accessibility needs of people who walk and bike. When we report statistics on collisions, for example, we follow federal guidelines around definitions and carefully specify the timeframe and other characteristics of the data so we can see trends, not just noise.

If we don’t think about the sources and uses of the numbers we get “data vomit”, a lovely descriptive phrase someone used in a workshop on Vision Zero evaluation at the 2018 Transportation Research Board annual meeting. Data vomit consists of spewing out every number whether or not it provides any actionable information.

And Now for the Rant

I was fresh off five straight days of absorbing academic research presentations at that TRB meeting (search #TRBAM on Twitter if you want to see just how much was going on in a convention center full of 14,000 people and over 5,000 posters, presentations, and workshops) when I spotted this:

When I saw it Friday night it already had 10 retweets, some of them from people I follow and respect. Sometimes I just hit the RT button for a quick share but I wanted to read more about the analysis behind the map. In my work we conduct crash data analysis on serious injuries and fatalities of people walking and biking and look at the behaviors, design factors and locations involved so I know there’s a lot to this, well beyond the raw numbers.

The linked article had no discussion whatsoever of the methodology, just a discussion of the nature of big, wide intersections that require more time for people to walk across. No argument from me on that point, but how did these specific intersections get identified? Well, there was a credit on the graphic that I could Google. And so the chase began.

It’s a long enough chase that I’m breaking this post into two parts. With this post I just ask you to look first at the real source of information before you share it.

Sharing is karma--pass it along!

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