My last post about the summer reading of “Open Government: Collaboration, Transparency and Collaboration in Practice” is inspired by two different articles.
The first one is “My Data Can’t Tell You That” by Bill Allison.
His article highlights a characteristic of open government that I have been writing about.
“In this brave new era of transparent government, more and more departments and agencies are publishing more and more of the data they collect online. Yet we are finding that, for this information to be useful, it requires a great deal of analysis and explication, and the how and why the data is gathered sometimes tells us as much about government as the information itself”
Indeed publishing more data does not equate to increasing transparency. On the contrary, flooding people with terabytes of raw data may cause more obscurity than clarity. Analysis as well as synthesis are important, and they can be performed both by government and third parties. So far the balance of open government has tilted toward the latter, assuming that non-government organizations as well as individuals can do a better job at bringing information to life.
The second article is “When Is Transparency Useful?”” By Aaron Swartz.
Aaron observes that
“A regulatory agency is a group of people whose job is to solve some problem. Transparency simply shifts the work from the govt to the average citizen, who has neither the time not the ability to investigate those questions in any detail […]
Hundreds of millions of dollars have been spent funding transparency projects around the globe. That money doesn’t come from the sky. The question is whether some transparency is better that none; it’s whether transparency is really the best way to spend those resources, whther they woule have a bigger impact if spent someplace else”
When the hype around open government will be over, questions will be raised about the rationale for spending on initiatives like “data dot gov dot wherever”. We should not forget that IT has rarely been seen as an asset to create greater and sustainable value. Therefore open government will have to compete with other IT and non-IT investments in a climate that will remain cost-conscious for the foreseeable future. Will it succeed in proving its value? Or will it fail and be challenged, as it happened to countless e-government projects?
Aaron gets closer to the crux of the matter:
“Data analysis can be really useful, not in providing definitive answers over the Web to random surfers, but in finding anomalies and patterns and questions that can be seized upon and investigated by others, not in building finished products but by engaging in a process of discovery”
Raw data do not do much by itself. It needs analysis and pattern discovery. Some of this can be performed by “others”, such as voluntary groups, activists, businesses, even individual citizens with a passion for government. Some can be performed by government employees themselves, in more open ways than with traditional reporting, but blending experience with willingness to innovate, and possibly merging internal and external effort through social media.
Aaron’s conclusion is quite powerful:
“Transparency can be a powerful thing, but not in isolation. So let’s stop passing the buck by saying our job is just to get the data out there and it’s other people’s job to figure out how to use it. Let’s decide that our job is to fight for good in the world.”
Open government is not a way to outsource problem solutions to others. It is a means to collectively solve problems more effectively and efficiently. Government and society are both data suppliers and users: they have to find the right blend for that data to create public value
Read Complimentary Relevant Research
Top Strategic Predictions for 2019 and Beyond: Practicality Exists Within Instability
Technology-based change is happening continuously, and most organizations struggle to see the change in advance. Continuous change can...
View Relevant Webinars
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.