Making dollars and sense of the open data economy

Is the push to free up government data resulting in economic activity and startup creation?

Open dataOver the past several years, I’ve been writing about how government data is moving into the marketplaces, underpinning ideas, products and services. Open government data and application programming interfaces to distribute it, more commonly known as APIs, increasingly look like fundamental public infrastructure for digital government in the 21st century.

What I’m looking for now is more examples of startups and businesses that have been created using open data or that would not be able to continue operations without it. If big data is a strategic resource, it’s important to understand how and where organizations are using it for public good, civic utility and economic benefit.

Sometimes government data has been proactively released, like the federal government’s work to revolutionize the health care industry by making health data as useful as weather data or New York City’s approach to becoming a data platform.

In other cases, startups like Panjiva or BrightScope have liberated government data through Freedom of Information Act requests and automated means. By doing so, they’ve helped the American people and global customers understand the supply chain, the fees associated with 401(k) plans and the history of financial advisors.

I’ve hypothesized that open data will have an overall effect on the economy akin to that of open source and small business. Gartner’s research has posited that open data creates value in the public and private sector. If government acts as a platform to enable people inside and outside government to innovate on top of it, what are the outcomes?

Over the past four years, the world has heard a rising chorus for raw data from voices like the creator of the World Wide Web, Tim Berners-Lee, and the chief technology officer of the United States, Todd Park. Park, in particular, has been working to scale open data across the federal government as the nation’s “entrepreneur in residence.”

McKinsey and Associates estimated the annual economic value of big, open liquid health data at some $350 billion annually. While that number is eye-opening, which companies and startups stand to change health care using open health data?

Some examples are clear, from mobile apps like iTriage (now owned by Aetna) to Castlight, but they aren’t sufficient to understand what’s happening out there.

Other promising startups are in the consumer finance space, where so-called “smart disclosure” initiatives are enabling people to put their personal data to use. Startups like and Hello Wallet now are enabling people to make smarter financial decisions.

I know there are more stories out there, and in sectors beyond health care and consumer finance — including transit, energy, education and media. Over the next several months, I’ll be identifying and profiling more civic startups, such as those from the first class in the Code for America accelerator, like Captricity, to specialized search engines, like Zillow, Panjiva and DataMarket.

In the course of that work, I hope to answer some big questions. What are the sustainable business models that successful civic startups are using, whether they use legislative data or other reuse of public sector information? ¬†What are the real costs associated with opening up government data to make it usable, both for government and entrepreneurs? And how does it balance against what datasets, at the federal, state or local levels, are the most valuable? Are they open and usable? If so, who’s using them and to what effect? If not, why not?

At the end of this particular project, in February, we’ll publish a report on what I’ve found. In it, I hope to be able to share some answers to several core questions on the topic. Where I need your help is in identifying new startups that are using or consuming government data or in highlighting how existing companies use it in their operations, good or services. Who is doing the most interesting work — and where? If you have research and evidence to share on the questions I posed above, feel free to ring in on that count as well.

Please weigh in through the comments or drop me a line at or at @digiphile on Twitter.

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