by Emma French
Governments at many levels collect large amounts of data every year through their programs and daily operations. Fueled by the belief that data produced by any government is the property of the tax-paying citizens, the open data movement seeks to make government data easily accessible and available to the public. Advocates argue that opening government data can increase government transparency and accountability, enable meaningful citizen participation in policy and decision-making processes, and spur economic growth and innovation in unforeseeable ways.
Open data policies are being passed all over the world to institutionalize the culture of open data and maximize the potential benefits derived from releasing data. In the last decade there has been a notable increase in the number of open data policies passed in the United States (see Figure 1 below). In 2006, Washington D.C. was the first local government to pass an open data executive directive. In 2009 the first of two federal open government directives was issued by the Obama Administration, and local policies were adopted in Memphis, Portland and San Francisco. According to the Sunlight Foundation there are now at least two federal, ten state, nine county, and 46 city-level open data policies in the United States.
Despite the importance of local policy, scant research has been done on the prevalence and effectiveness of open data policies at the city level. In an attempt to fill this gap, CUI researchers recently conducted a study to examine the variation that exists among city level open data policies in the United States. Twelve policies were assessed based on their potential to increase transparency, public participation, and economic innovation (Table 1).
Table 1. Selected Open Data Policies
|City||Population (2015)||Year of Adoption||Legal Means
|Implementing Agency||Stated Policy Purpose|
|304,391||2014||Ordinance||Open Data Management Team (new team incl. reps from each city dept. and chaired by the Chief of Innovation and Performance)||Transparency; cross-sector coordination; local software innovation; government efficiency; open by default|
|410,939||2014||Ordinance||Open Data Advisory Group (new team incl. Chief Information Officer and Open Data Coordinator from each dept.)||Transparency; government efficiency; public participation; economic innovation; social progress; collaboration|
|Kansas City, MO||475,378||2015||Ordinance||Chief Data Officer (reports to the City Manager)||Transparency; Innovation by government, public or other partners|
|403,505||2015||Executive Order||Open Data Advisory Board (new team)||Transparency; public participation; efficiency; economic opportunity|
|176,588||2014||Executive Order||Open Data Advisory Group (new team incl. the Chief Information Officer and reps from each city agency); Office of Open Data and Performance Management (created 2015)||Transparency; civic engagement; economic development; improved coordination and efficiency among cross-sector organizations|
|298,550||2014||Administrative Regulation||Open Data Working Group (new team incl. Open Data coordinators from each of the city’s departments); Open Data Executive Committee (new team diff. from Open Data Working Group)||Transparency|
|Baltimore, MD||621,849||2016||Ordinance||Chief Data Officer; Department Open Data Coordinators||Innovative uses by city agencies, the public and other partners|
|San Francisco, CA||864,816||2013||Ordinance||Chief Data Officer; Department Data Coordinators||Transparency; mobilize high-tech workforce to create civil tools and applications; social and economic innovation; empowering citizens to participate; job creation; public-private partnerships|
|New York City, NY||8,550,405||2012||Local Administrative Law||Department of Information Technology and Telecommunications||Transparency; intra- and inter-governmental interoperability; public participation; innovative strategies for social progress; economic opportunities|
|Washington D.C.||672,228||2014||Executive Directive||Chief Data Officer (CDO); Open Government Advisory Group (new group incl. Mayor’s designee, the Chief Data Officer, and Director of the Office of Open Government)||Transparency; public participation; collaboration; effective government; economic development; public trust in government|
|827,097||2015||Administrative Policy||Department of Innovation and Technology (existing group)||Transparency; civic engagement; economic development; investment; public confidence in government|
|2,296,224||2014||Administrative Policy||Enterprise Data Officer (EDO); Open Data Advisory Board (new group)||Transparency; civic engagement; cross-sector collaboration; efficiency; societal improvement; economic growth|
The policies were analyzed by controlling for the transparency of the process through which they were created (open vs. closed) as well as the size of the city in which they were created (small vs. large). Ordinances were included in the open policy creation category, and executive orders and administrative policies comprised the closed category.
Three indexes were developed using proxies to assess the potential for each of the policies to increase transparency, public participation and economic innovation. For this study transparency is defined as the willingness of a government be open and accountable to the public. Public participation is the degree to which citizens are meaningfully involved in government policy and decision-making processes. Economic innovation is the degree to which citizens, entrepreneurs, and businesses are empowered to produce new innovative services and products. Table 2 below lists the indicators used for each index. Indicators with ‘SF’ by them were borrowed from the Sunlight Foundation’s Open Data Policy Guidelines.
Table 2. Indexes for Evaluating Open Data Policies
|Proactively release government information online (SF)|
|Create a public, comprehensive list of all information holdings (SF)|
|Specify methods of prioritization of data release (SF)|
|Stipulate that provisions apply to contractors or quasi-governmental agencies (SF)|
|Create central location for data publication (SF)|
|Require publishing metadata (SF)|
|Appropriately safeguard sensitive information (SF)|
|Public Participation Index|
|Incorporated public perspectives into open data policy making process|
|Require incorporation of public perspectives into policy implementation (SF)|
|Mandate data formats for maximal technical access (SF)|
|City has created an open data portal|
|Citizens can request new data via the website|
|Citizens can ask for help with data use via the website|
|City has offered free trainings on data access and use|
|Economic Innovation Index|
|Place data in the public domain or make available through an open license (SF)|
|Portal has an API to encourage developers to use the data|
|Competitions or hackathons to encourage use|
|Create/explore potential partnerships with other governments or institutions (SF)|
This study’s findings support the claim that on average open data policies created through an open process have greater potential to increase transparency, public participation, and economic innovation than those created through a closed process. On average policies in larger cities scored higher in terms of transparency and economic innovation, however policies created in smaller cities scored higher in terms of their potential to increase public participation. Barriers to successful open data policies include restrictive licensing, closed formatting, privacy concerns and uneven access to the technology and knowledge to use open data. Policies that embrace meaningful transparency, public participation and cross-sector collaboration can support the creation of urban innovation ecosystems that promote use of open data.
Recommendations for governments creating an open data policy
- Address privacy concerns directly and proactively
Critics of open data will try to use this as a way to prevent opening up access to public data. In order to minimize this barrier it is critical that cities address privacy and security concerns up front.
- Be open, but also strategic
In order to realize the full economic and innovative potential of open data, open data policies need to require open formatting of data that allows for easy use, re-use, and integration. Data should be dedicated to the public domain or made available through an open license. Cities should make sure that restrictions are limited in order to maximize the potential for the data to be turned into public value. At the same time, it is important to be strategic when crafting policies and plans.
- Great policies aren’t enough
In order to transform open data into public value, cities need to collaborate across sectors and political jurisdictions. They need to start thinking about the public not as a client, but as a potential partner whose personal experiences can help inform the city’s work. The focus needs to be less on the supply-side, and more on the demand-side (Janssen, Charalabidis, and Zuiderwijk 2012; Conradie and Choenni 2014). Cities should be intentional about creating a culture of openness internally in order to nurture an ecosystem for open innovation more broadly (Schaffers et al. 2011).
Open data has no intrinsic value; rather, its value is dependent on its use. Open data policies can support cities’ efforts to increase transparency, public participation and economic innovation. However, policies alone are not enough to achieve these goals, and in some cases they may actually inhibit such innovation from taking place. The findings from this study support the claim that open data policies created though open processes have, on average, greater potential to increase transparency, public participation, and economic innovation than those created through a closed process. Cross-disciplinary and cross-sector collaboration were identified as integral to promoting greater interoperability and to expanding use of open data to support innovation. Future research is needed to evaluate the effectiveness of city-level open data polices, and to better understand the processes through which open data is used to create public value.