Mining Federal Procurement Data for Companies and for Profit


GovTribe sees an opportunity in helping firms navigate the messy world of government contracting.

Open data is often compared to a natural resource. What that typically means is that just as oil and gas form naturally as a part of earth’s geological processes, so data grows naturally from the processes of government and industry.

The metaphor works another way, too, though, according to GovTribe CEO Nate Nash. Just as gas and oil must be refined before they become valuable fuel, government data must be combined, mashed up, massaged and manipulated to bring value to businesses, watchdogs, consumers or citizens.

Nash used to work through the unrefined -- or only lightly refined -- version of U.S. government contracting data as a consultant for Deloitte’s federal government practice. In 2012, Nash and two Deloitte colleagues launched GovTribe, a company that takes contracting data from notoriously messy government websites and transforms it into a clean, mobile interface where contractors can search for and track opportunities using keywords. GovTribe subscribers can also search by a contractor’s name to keep tabs on what their competitors are doing.

Nextgov is taking a closer look at GovTribe’s experience this month in our Government Data Unbound series, which profiles companies and nonprofits that are helping turn open government data into a multi-billion dollar industry.

Because the government only releases some of its contracting data in bulk, streaming form, GovTribe built complex programs to scrape content from sites such as the Federal Business Opportunities website and make it searchable through the GovTribe iPhone and iPad apps.

If Nash could press one reform on government contracting data, he said, it would be to make them machine readable up front so data entrepreneurs only have to worry about adding value to the data, not accessing the data.

“It’s government’s responsibility to make these data as easily consumable as possible, especially by machines,” he said. “From there forward, anyone can innovate on top of those data.”