Last week’s Open Cities conference, sponsored by the Rockefeller Foundation and Next American City, brought together a diverse group to discuss the role of new media in shaping urban policy. One of the major topics discussed was the emerging trend of cities establishing data catalogs where a wide range of datasets and feeds are made available, often with the explicit goal of enabling private apps that will use the data to create value. Washington, D.C.’s data catalog is a national leader, and San Francisco, Boston, and others not far behind. (Through sheer coincidence, New York City announced their BigApps contest during the conference.) In addition to the city-led programs, a host of other sources — from Google Transit to Data.gov — are making urban data more available than ever.
Within government, data can be a powerful tool for management and service delivery. Baltimore’s CitiStat and its emulators have shown the power of data to focus on the bottom line for easily quantified government services and policies. Applications for e-management within government are many, and today’s New York Times story on IBM’s Smarter Cities initiative describes several.
Outside of government, the case is less clear. Some at the conference questioned whether governments should expend their limited resources on finding, cleaning, and publishing data. I think this debate is largely won. The costs of hosting data has dropped precipitously, most of the datasets have already been purchased by citizen tax money, and the resulting apps really do seem to create new value for city residents. Less clear, however, is whether disclosing data to the public will have any impact on urban policy.
It is this deeper question that lurks in the background of conversations about data: although more and more may be available, does influence urban policy or planning? A conference attendee who works for the mayor of a major east coast city suggested this at one point: in his opinion the city was driven by politics, not data.
On the one hand, data seems very needed in planning. Urban planners analyze data to understand trends, and every city plan contains detailed tables, charts, and data analysis. Outside government, community development corporations and nonprofits are also frequent data users: for grant applications, advocacy, and to explore trends in urban neighborhoods. In fact, hundreds of government planners, nonprofit employees, community activists and citizens came to the conference I helped organize here in Boston last summer titled “Data Day: Using Data to Drive Community Change.”
However, the cynic will retort there are “lies, dammed lies, and statistics.” Certainly, government planners and activists need data, the argument goes, but it’s just to support their particular agenda or policy. Taken to the extreme, this jaded view says you can find statistics to back up any belief.
This wasn’t always the case. In fact, for a brief period in the 1960s there was a great deal of interest about the possibility of establishing “social indicators” analogous to economic indicators. Just as economic indicators, such as unemployment rate, are used to determine economic policy, social indicators would guide social policy. Judith Innes in her 1975 book Social Indicators and Public Policy argued social indicators could be created, but must rely on a consensus understanding of definitions and measurement. The book’s fascinating history of the unemployment rate shows how the measurement has responded to cultural values about who to count. Despite thousands of books and articles on indicators in the late 60s and early 70s, the movement didn’t take off as expected. Defining social indicators was value-laden, collecting social data expensive, and focusing on data seemed irrelevant to a turbulent, problem-filled world. It’s little wonder when the second edition of Innes’ book appeared in 1990 it was re-titled Knowledge and Public Policy.
Although falling short of her definition of an indicator, many government datasets do provide a common framework for discussion and analysis, even perhaps guide policy creation. Although often imperfect, their flaws are well known by all users. In the 1990s, a number of “indicators” projects emerged, organized as the National Neighborhood Indicators Partnership. Generally based in nonprofits or foundations, these projects took advantage of new technology and plentiful government data to track measures of their choosing. (At MAPC, I worked closely with the Boston affiliate – the Boston Indicators Project)
Today, thanks to rapidly evolving technology more urban data is available than ever. Its role is equally ambiguous, simultaneously in demand by diverse users to use for advocacy, government service delivery, and perhaps crafting urban policy. At the conference, federal officials reminded the group the Obama administration is interested in evidence based governance, and President Obama even elevated the former architect of the D.C. data catalog, Vivek Kundra, to the nation’s first Chief Information Officer. In an interesting way, perhaps during times of concern for the public interest we are more likely to view data as a shared resource for deliberation and discussion of new policies and plans. We may be in a new era of data availability, but as always what matters isn’t the numbers themselves, but how we view them.