Open data innovation capabilities: Towards a framework of how to innovate with open data

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Abstract

Innovation based on open data lags behind the high expectations of policy makers. Hence, open data researchers have investigated the barriers of open data publication and adoption. This paper contributes to this literature by taking a capabilities perspective on how successful open data re-users create value out of the available data sources. First, a framework of IT, organization and skills capabilities required to innovate with data is derived from literature. Second, a case study including a survey and interview with managers from 12 frontrunners in the Netherlands was conducted. The analysis reveals that skills are valued the highest closely followed by organizational capabilities. Setting up a multi-disciplinary team with motivated employees and giving this team the mandate to experiment with data, is essential when innovating with open data. Theoretically, this study contributes to open data research by offering a new capabilities perspective on the organizational level. Our results highlight the importance of entrepreneurship theories to explain value creation with open data. Practically, our study suggests that digital skills and start-ups are important to the open government data policies.

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APA

Eckartz, S., Van den Broek, T., & Ooms, M. (2016). Open data innovation capabilities: Towards a framework of how to innovate with open data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9820 LNCS, pp. 47–60). Springer Verlag. https://doi.org/10.1007/978-3-319-44421-5_4

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