SUDS Summer Spotlight

Hard to believe there’s only one month left of summer… Curious where in the world it’s taken SUDS members? Read below to find out a few of cool things our crew has been up to:

Krista Kinnard, MS Public Policy & Management-Data Analytics, 2017
Krista Kinnard
1) Where are you working/researching/interning?
LMI, Washington D.C.

2) What does your work station look like? (e.g. Google pod, classic cubicle, etc)
Traditional cube with many “team rooms” available for collaboration and brainstorming.

3) How would you describe your main responsibilities/projects in two sentences (or one long one, with lots of commas)?
I work predominantly with insurance provider compliance with Affordable Care Act regulations. We receive data from all insurance providers on the exchanges (both federal and state) and evaluate them to ensure they are providing adequate coverage to individuals seeking health insurance through healthcare.gov. One interesting project I am working on is using Python (mostly the Pandas library) to weed through all of the individual physicians listed on the exchange through these insurance providers and identifying the languages they speak in their practices. Eventually, I will be creating a map of these languages and organizing the data in such a way that it can be included in a larger database for individuals choosing insurance plans on the exchange to be able to access physicians in their insurance network that speak their language.

4) What’s one insight about data/policy you’ve gained from your work so far?​
You can spend your entire life cleaning data

5) What’s your favorite summer after-work activity?
Exploring D.C.!

Lauren Renaud, MS Public Policy & Management-Data Analytics, 2017
Lauren Post
1) Where are you working/researching/interning?
Larimer Consensus Group in the Larimer neighborhood of Pittsburgh, just past East Liberty

2) What does your work station look like? (e.g. Google pod, classic cubicle, etc)
We’re located in the ECCO Center, a green building on Larimer Ave. The main room when you walk in has a long desk running around the edge of the room. I sit there with my laptop.

3) How would you describe your main responsibilities/projects in two sentences (or one long one, with lots of commas)?
Building maps, web tools, and analysis that will inform smart growth development and a single family housing strategy.

4) What’s one insight about data/policy you’ve gained from your work so far?
You learn so much more by having to do it every day. I’ve been jumping between ArcGIS, CartoDB, and R to clean and visualize our data. There’s not necessarily one “best” tool for the job, just use what you know and figure it out as you go.

5) What’s your favorite summer after-work activity?
Exploring Pittsburgh in the summer by bike

Justin Cole, MS Public Policy & Management-Data Analytics, 2017
1782364
1) Where are you working/researching/interning?
MetroLab Network; Washington, DC

2) What does your work station look like? (e.g. Google pod, classic cubicle, etc)
Most of the time a windowless office, but occasionally the eclectic confines of one of DC’s great coffee shops.

3) How would you describe your main responsibilities/projects in two sentences (or one long one, with lots of commas)?
I’m working with representatives from government, philanthropy, and higher education to develop strategies for long-term funding and programming of a smart cities network. The network is committed to an RD&D model to partner research and development from universities with rapid deployment in metro areas to solve some of the nation’s biggest urban challenges.

4) What’s one insight about data/policy you’ve gained from your work so far?
It’s difficult for cities to be the first to try a new data-driven approach or adopt a new policy that changes the way things have already been done; yet there’s an incredible network of public leaders out there working to share best practices and help all cities push new ideas forward.

5) What’s your favorite summer after-work activity?
Going for a run on the National Mall (even with the heat and humidity of DC’s swampy summers).

 

Want to share your summer experience? Answer the questions above and email us!

Data Skills Workshops recap: javascript viz and open city data

Thanks to everyone who’s been joining our SUDS Data Skills Workshops this semester! So far, we’ve heard from Alex Sciuto on using Javascript and D3.js for data visualization, and Bob Gradeck from the Western PA Regional Data Center on finding and using city data. It’s been awesome to dive into the many tools and resources out there that we can use to tackle our data dreams (or nightmares…). And we’re so grateful to have these gurus share with us!

20160217_175556

Bob Gradeck schooling us in the ways of open city data

dataviz example

Example of a D3.js vizualization

Here’s a link to Bob’s hot tips on city data and to Alex’s presentation on GitHub (seriously great stuff in here).

We’ve still got a stacked deck of workshops remaining for the semester, including:

Hope to see you there! As with all SUDS events, workshops are free and open to all (including non-students).

And a big thanks to Krista Kinnard for coordinating our workshops! If you have any ideas for more topics, please contact us at info@suds-cmu.org.

 

SUDS tours Google: better cities through public-private data partnerships

Last Wednesday, SUDS visited Google’s Pittsburgh office, on the eve of its 10-year anniversary celebrations. We got to see their famous hammock room, Kennywood-themed hallways, and micro kitchens stocked according to behavioral science. But as jealous as we were of the nap pods, the best part of the visit was a talk by CMU Computer Science PhD alumna Sarah Loos on Google’s Better Cities project.

Cities face huge challenges in monitoring and managing their transportation infrastructure. In the US alone, $124 billion is wasted each year in traffic jams. The Better Cities team at Google has been piloting methodologies that match up cities’ transport data with aggregate, anonymized snapshots of historical traffic statistics in order to yield insight and solutions to nasty traffic problems.

For example, Google partnered with the City of Amsterdam to validate sensor readings on the A10 highway, which can tell when cars are slowing down (and thus, if a traffic jam might occur). The city can then analyze the data and change speed limits on its digital signs and take other measures to mitigate the jam’s impact. The physical sensors are really accurate, but also really expensive to install and maintain. Google found that by combining only some of the sensor data with representative models of aggregate data, it could detect the same traffic patterns with a high level of accuracy. By reducing the number of sensors needed in each stretch of road, Amsterdam’s government can save between 50,000-100,000 Euros per kilometer per year.

 

As cities are using more individual-level data from more sources, including public-private partnerships, Loos stressed the importance of keeping information anonymous and private. Her work is focusing on differential privacy algorithms, which add enough noise to the data to mask the influence of any one individual’s contribution to the set.

These pilot projects are an exciting example of how simple, but smart, data collaboration can improve city management. And Loos and her Google team are looking for new cities to partner with—we hope Pittsburgh will be one of them!

20160120_165752