Open data has become a buzzword within certain circles.
It increasingly serves as shorthand for the movement to increase government transparency through openly accessible civic data in standardized formats.
Following the revelations of large-scale NSA surveillance and decreased transparency at the higher levels of government, critics question the efficacy of open data efforts. But, many such critiques of open data initiatives are reductive, mistaking one aspect of the community for its totality. Beyond efforts to make local, state, and federal data more accessible to the public, people are working for greater access to useful data from other large institutions such as academic, medical, or philanthropic organizations.
Some of the most compelling correlations are found in the mashing up of useful data from a variety of sources. It’s one thing to map crime incident data, but much more illustrative to contextualize these incidents with socioeconomic data. It’s sobering to visualize the increase in diabetes in the United States, but more useful to consider how access to fresh food might influence the rise of the disease in certain areas. Census data may identify socioeconomic inequity, while tracking campaign donations might suggest potential corruption. The most compelling data stories emerge in the connections between various data sets from different sources.
Those stories can increase citizen awareness and engagement, reveal unexpected insights and correlations, and even effect policy change. Martin Tisne, director of policy with the philanthropic investment firm Omidyar Network, writes about this virtuous circle at the Open Knowledge Foundation blog:
…it’s the connections between the data sets that are powerful and interesting. You may not care so much to know where most people under 15 years old live in your country, but if you’re told that those that live close to a nuclear waste disposal site happen to have the highest cancer rates, then it becomes seriously relevant. Same as above, techies often talk about technical data standards and get quizzical/skeptical – at best – looks in exchange. But technical data standards are the fuel that allows policy wonks to compare data sets, which creates relevant data. Connecting the dots makes it policy relevant – without data, you can’t make policy.
It’s important to remember that the open data community doesn’t represent a single special interest group. It’s instead a motley bunch of developers, researchers, journalists, hackers, entrepreneurs, activists, philanthropists, and many more. Some of its members’ goals and motives are shared, while some are at odds. A decrease in transparency at one level of government doesn’t represent a failure of open data as a whole, nor should it discourage ongoing efforts to increase transparency of various institutions. More accessible and usable data prompts new questions, enable better models, and yields great insights and promise for society as a whole.