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Highlights from Data Innovation Across America

by Travis Korte
A photo from the train during Data Innovation Across America

Somewhere between the harrowing, rush-hour escape from Mountain View, CA and the picture I snapped with a stats legend in Pittsburgh, PA, I caught a glimpse of America’s data landscape.

As a participant in the inaugural Millennial Trains Project, I traveled by rail to visit seven cities in ten days, exploring innovative data initiatives and emerging policy concerns with government, industry and academic leaders.

I will be sharing some interviews and blog posts from the trip over the coming weeks. In the meantime, here is a summary of the highlights.

Bay Area

Salt Lake City

  • Talked about the future of data centers with secure data storage firm Space Monkey.
  • Spoke with a legal scholar about the barriers to open access and the vision of research data sharing.
  • Mulled over the cultural obstacles to data-driven philanthropy with Arabella Advisors.
  • Chatted with Ancestry.com and learned what it was like to develop ad-hoc parallel computing solutions before the advent of Hadoop.
  • Brainstormed the implications of data-driven private equity with a local VC.
  • Spoke with the founder of one of the earliest private cloud storage providers about how managers can age gracefully in the face of new technology.
  • Attended a pitch session featuring a crafty, signal processing solution to water infrastructure decay.




  • Met with Chicago’s Director of Analytics to discuss the city’s developer community and data integration strategy, and brainstormed the steps other cities might take to adapt Chicago’s successful model.
  • Got a crash course on the major forces in Chicago’s data scene from Smart Chicago, and learned about some of the data-driven startups it has supported.
  • Learned how urbanists at the Metropolitan Planning Council are mapping city data to prioritize civic infrastructure projects.


Washington, D.C.

  • Began synthesizing everything I learned into key policy insights.

The cities I visited offered a couple of major lessons.

First was the importance of a strong executive in the development of a metropolitan or statewide data science community. In cities like Chicago and Oakland, the mayors have been extremely proactive about creating positions for data management officials and giving their blessings to civic hacking events. A well-crafted executive order may be all that’s standing between a city and its dormant developer community.

Second, stakeholders in several cities stressed the importance of convening; the easiest way to foster a healthy civic data infrastructure may simply be ensuring that local developers are acquainted both with one another and with government staffers and locally-minded nonprofits. Even if a hackathon doesn’t produce many useful apps, it can still be an extremely effective way to introduce and encourage collaboration between people who wouldn’t otherwise know each other.

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