I recently attended the 2018 Association of Public Data Users (APDU) conference. This was my second time attending the conference, and I enjoyed learning more about how other people use federal statistics. Some of my favorite presentations were:
- Julia Lane on her experience teaching Big Data to social scientists and government workers.
- The Bureau of Economic Analysis (BEA) on their R package.
- Aaron Klein on the value of policy makers getting realtime data
Julia Lane and the Coleridge Initative
As an “R guy” I’m normally the odd man out at APDU. While many attendees do work with data, they tend to use GUI-based tools such as Excel and Tableau. I’ve often wondered if any of the attendees would benefit from learning programming language-based data tools such as R or Python.
It turns out that Julia is the author of an entire book on this topic: Big Data and Social Science! She is also a director of the Coleridge Initiative, which provides Python-based data analysis training to government workers and social scientists.
Julia spoke about her experience with these projects, and the results seemed very positive!
The Bureau of Economic Analysis (BEA) has an R package
While I mostly blog about data that the Census Bureau publishes, APDU is a great reminder of how many other statistical agencies there are. An example is the Bureau of Economic Analysis (BEA) which, among other things, calculates Gross Domestic Product (GDP) statistics.
BEA was a sponsor of the conference, and I got to chat with one of the people running their booth. I was surprised to learn that BEA has published their own R package: bea.R. This is the first time that I have heard of a government agency developing their own R package!
The person I spoke with mentioned that BEA’s Chief Innovation Officer, Jeff Chen, is a big proponent of R. You can learn more about the BEA here.
I think that it would be interesting to extend Choroplethr to work with data from the BEA.
Aaron Klein on Policymakers Getting Realtime Data
Aaron Klein, a former Treasury official, spoke about the value of policy makers getting realtime data. Aaron worked in Treasury during the foreclosure crisis, and spoke about the challenges policymakers faced in responding to it. One issue was quantifying the impact that foreclosures and abandoned homes have on broader communities.
He recently wrote a research paper that attempted to answer this question: Understanding the True Costs of Abandoned Properties: How Maintenance Can Make a Difference. One statistic from the talk left a big impression on me: vacant residential buildings account for one of every 14 residential building fires in America. When you consider that only a small portion of residential homes are vacant, this statistic is truly startling.
Having data like this at the start of the foreclosure crisis might have improved how policymakers responded to it.