The directive, sent to the head of every federal department and agency today, instructs the agencies to take specific actions to open their operations to the public. The three principles of transparency, participation, and collaboration are at the heart of this directive. Transparency promotes accountability. Participation allows members of the public to contribute ideas and expertise to government initiatives. Collaboration improves the effectiveness of government by encouraging partnerships and cooperation within the federal government, across levels of government, and between the government and private institutions.--Read more at the Open Government BlogOut of the box, much of the specifics in the Directive was focused on transparency and the opening of public data sets. For example, in 45 days, three heretofore unreleased high value data sets need to be available on data.gov. [Sunlight Foundation parsed the directive and published a timeline for agency requirements.]
Requirements for collaboration and participation are less specific. [See Nancy Scola's very good summary and analysis on the Directive content on Tech President.]
Getting ready for collaboration and participation is what I wanted to talk about.
There's been plenty of work on engaging with the public--from the March Open for Questions exchange fueled by people submitting questions and voting for the ones they wanted the President to answer to the development of the Directive itself.
Chris Brogan is a well-known new media marketing guy. He suggests that people try and think like "-ologists" and learn from -ologists (anthropologists, sociologists, psychologists) in their outreach. Check out his 45 second video.
It's critical for government to take a broad look at how we interact, how people interact, and what it might mean. Taking a structured analytical approach--dare I say scientific--becomes critical. Open government efforts need to be structured to include measurement and evaluation. Best practices can't be defined without understanding the variables and the inputs. Did we get a good result because we were lucky? Did we get a good result because we think we did? Or, did we get a bad result that we believe is good? Did we get a good result because we went into the experiment as an -ologist?
This post was inspired by a reference in my Sunday paper to "Web-Based Experiments for the Study of Collective Social Dynamics in Cultural Markets" (PDF). The authors, sociologists Salganik and Watts, provide some perspective on how the idea of popularity can influence what is popular. The researchers found that there is randomness in the creation of popularity within a network. A song, for example, becomes more popular as other people in the network show interest. In another network, a different song could be the winner. That's why it's hard to predict the next hot song, band, movie or toy. It's somewhat random and unpredictable.
The got me thinking about how important network dynamics are to spreading ideas, forming consensus and developing meaningful interactions. Meaningful for citizens as well as government. And, it got me thinking that people are already studying these patterns in other venues.
This isn't getting any easier.