The costs of open geospatial data (Johnson et al. 2017)

Open data has become a big movement in local governments. This article raises concerns over the costs incurred in the process of government data provision. The idea that making government data freely accessible – especially when geospatial data is involved – would create direct and indirect costs.

The authors suggest that direct costs must include considerations of individual privacy and confidentiality. Indeed, privacy protection may create direct costs, but government officials must ensure that all open data respects and only discloses information that cannot be attached to individuals. For instance, journey data is being used in a variety of ways to create and improve geospatial data products and to deliver services to uses. The journeys people take can be used to infer where they live, where they work, where they shop. If individuals become unwilling to share movement data, then this will impact the ability for that data to be used in ways that create economic and social benefits.

Besides direct costs, Johnson et al. (2017) identify four areas where the provision of open geospatial data can generate unforeseen expenses. They indicate that the private sector pushes for the release of “high value” datasets to develop their commercial products or services. This could divert governments’ attention from “low value” data. However, note that high-value data could also have a significant impact on citizens. People are taking advantage of applications that made use of open data. Transit commuters know how long they’ll be waiting for a ride. Drivers easily find parking close to where they want to travel to. Renters get detailed information about crime and school for any address. The information that developer access to inform these applications come directly from high-value datasets.

One way to reduce costs is to limit what data sets are published. Public officials tend to focus on the number of datasets they release rather than on the effect of releasing high-quality sets of data. Cities should do a careful analysis of which datasets have the most impact, both in terms of social and economic benefits, so as to avoid hidden costs.

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