For those who haven’t heard me rave before, NNIP is a national network of organizations that share a commitment to creating and maintaining neighborhood-level data systems and helping their communities use the information to make better decisions. We meet up twice a year to talk about our data shops – new discoveries, advances in analysis and online tools, challenges we’ve encountered, and much, much more. D3 has been a proud partner organization since 2009. Partners take turns hosting the meeting, and this time we went to Denver, Colorado, where the Piton Foundation makes data come alive through their Data Initiative.
As always, I learned so much last week from all of our partners in the network. Here are some of the highlights I took away…
Nonprofit does not mean we can keep going without funds!
(A quick aside: I’m using the term nonprofit here, but I agree with Doug Bitonti Stewart of the Max M. and Marjorie S. Fisher Foundation that we need find a new term for our sector such as the “for impact sector”. Why should we define ourselves by what we are not, versus what we are for?)
As D3 approaches its sixth anniversary, we’ve been doing a lot of thinking here about how we fit into the local environment, how we can best serve our community through the products and services we provide, and how to ensure D3 can continue to serve our community over the long haul. As we grow up, we are also turning our data-driven philosophy inward and discovering some really important information about ourselves.
Taking a data-driven approach on the inside as well as out is certainly not new among the national partners, but it seemed to be a common theme of our meeting this fall. Many of us are working through formulating business models, diversifying funding streams, monitoring internal performance, and understanding external impact. Check back in the near future to read more about what D3 is learning through our investigation and analysis.
Our partners are building awesome online tools
Greater Portland Pulse is demonstrating incredible potential for regional collaboration and metric tracking for a region comprised of seven counties in two states.
My hands down favorite illustration of the uncertainty we should feel when using American Community Survey (ACS) data: The Randomizer. The tool generates random values for households in poverty by census tract between the range of possible values given by ACS, and a resulting total value of the households in poverty based on the tract numbers generated. Thanks to John Garvey for sharing his creation with me, and to Urban Strategies Council in Oakland for always pushing the cutting edge.
We can all be powerful data advocates
As John’s tool depicts, American Community Survey (ACS) data can present some challenges when presenting data for small areas. It seems I find myself engaged in multiple discussions at every NNIP meeting about ACS data: to use or not to use? Are the data reliable enough or just garbage? Should we replace ACS with locally sourced data, data which may be more accurate, but less comparable to other places and much more time consuming to produce for more than one jurisdiction?
I didn’t walk away with any clear answers, but I do know one thing: if we appropriately fund the ACS as a nation the data would be more reliable than they are now, which is important not only for the annual $400 billion in federal and state fund disbursement which relies on the data, but also for all the community development and planning work that goes on every day at a local level across the country. Congress appropriates ACS funding – let your congressperson know you care! And I beg you – if you are lucky enough to receive an ACS questionnaire, please fill it out! I’m still waiting for mine…
NNIP data advocacy work extends beyond government or administrative data use, it also includes maintaining open data sites and convening data user groups. D3 only recently launched our Open Data Site, but some partners have been publishing open data in their respective cities for years. Some have even developed sophisticated user groups, trainings, and conferences to more broadly engage their communities in the practical use and application of data. Why is this so important? William Gibson put it best: “The future has already arrived. It’s just not evenly distributed yet.”
Baltimore, Columbus, Indianapolis, and the MacArthur Foundation (on behalf of the Chicago School of Data) shared with us their experiences with local user conferences during the last day of the meeting. I still have much to digest and apply to D3’s trainings and advocacy for improving data literacy, but in the meantime, I’ll suggest readers refer to NNIP’s putting open data to work in communities.
Thanks NNIP for gathering us all together once again!