Open data and bureaucratic thrift

After reading through both of the articles this week, I’m reflecting on previous conversations and experiences I have had with open data and government access. I was especially impressed by the thoroughness of the “5 Myths” section of Janssen et al, which did an excellent job of unpacking some of the rhetoric and misinformation surrounding the current trend of open government data.

In reading both, I did feel that one aspect of open data was especially under-addressed, and could be explored further – the cost-saving factor motivating governments decisions to release open data to the public. As the size of the data sets local and national government actors manage has grown, the burden of managing those has increased. Keeping this data private and making careful decisions about who has access, what requests to authorize, and how to manage it quickly becomes a bureaucratic leviathan as the data sets exponentially increase. By making these data sets public, the labor and infrastructural costs of managing information access requests are massively reduced, making the governments work far easier. Many governments have adopted a policy that data is by default “open”, and unless policy makers and data managers specifically believe a certain data set should be private any new information generated is immediately available for public dispersal.

This dynamic has been explained to me multiple times by policy-makers at the city level, and I have personally seen its efficiency. In many ways this cost saving motivation provides more support for the argument at the center of Robinson et al, which is that data is better left in the hands of outside actors whereas it is the governments responsibility to ensure that what data is accessible is easily managed. The previous comment stated that “Public officials tend to focus on the number of datasets they release rather than on the effect of releasing high-quality sets of data.” I believe that the best explanation for this decision is the cost-saving factor I outlined above.

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