The Effects of Open Data Communities on Open Data Benefits and Barriers

Abstract

Governmental organisations worldwide are working on their open data strategies and are openly sharing their data with the public. Recently also open data communities have been set up by several national governments. The effects of setting up these data communities on open data benefits and barriers and whether an effect exists at all is not yet clear, because there has been little scientific research into data communities. This thesis therefore focuses on the effects of setting up open data communities. 
A single-unit case study was conducted to gather qualitive information of the effects of data communities. The case study focussed on the Dutch open data community and consisted of two parts, a document analysis and in-depth interviews. The results of the analysis show how the Dutch community contributes to enhancing open data benefits, including (indirectly) creating more informed citizens, increasing the access to capacity and resources outside of the data publishing organisation and a higher problem-solving capacity. Furthermore, the interview participants agree to a large extent that communities contribute to intragovernmental collaboration and the use of collective intelligence to solve public problems. According to the interviewees, the community also (potentially) mitigates open data barriers such as the lack of interest in using open data (by governmental organisations). The interviewees stated that the community managers made sure every question that was posted got a sufficient answer within a reasonable amount of time and therefore the barrier stating that the data provider ignores requests and suggestions of data users could also be mitigated, as well as difficulties in the interaction with the data provider. Both researchers and most community users and managers argued that the community could also contribute to mitigating low engagement of public managers with open data and increasing the knowledge and skills of employees to use the open data. Lastly, according to the interview participants, the community can decrease difficulty in discovering/locating data and not being able to combine and connect datasets. The interviewees were also questioned about how institutional instruments could increase the value of the open data community. Although the participants concluded that the contribution of formal instruments (such as rules) is limited, they indicated informal rules (such as norms) and enforcing instruments (such as rewards) can contribute to the value that is created by an open data community. 
The community-specific challenges identified in the analysis can contribute to the process of designing an open data community, because policy makers can compare scope and design choices with the empirical experiences. This thesis also provides an exploratory scientific contribution: this research provides insight into how open data communities can contribute to enhancing open data benefits and the mitigation of open data barriers. Although the results are promising, certain limitations are applicable to the research. The thesis only studied one open data community and the full list of open data benefits and barriers was reduced based upon an assessment of the author of the thesis. Last of all, the interviews focused on qualitative data. Combining the results of this thesis with other case studies can improve generalisability.