Open Data Innovation, What are the Main Issues/Challenges for Open Data Projects in Sweden: An Abstract
The Internet has greatly reduced the cost of collecting, distributing, and accessing information, services, and resources. In parallel to this advancement, open data in both the private and public sector has gained attention in recent years, although the concept of open data is not new. Advocates have been arguing for years that data gathered or created by a government institution and funded by public money should be ‘open’ or free of any restrictions.
There are very limited studies on open data, with a particularly notable ‘lack of refereed, rigorous, and independent academic studies beyond a government and consultant ‘grey’ literature of mixed quality’ (Gauld, Goldfinch & Horsburgh, 2010, p 177; Ohemeng & Ofosu-Adarkwa, 2015, p 420). This study has two main objectives: it attempts to understand (1) how open data, especially government data, can create value for its stakeholders and (2) main issues/challenges within open data-driven projects, so that the expected potential of open data innovation be captured.
Swedish Innovation Agency, Vinnova, had open data calls to fund open data projects. Sixteen project managers were interviewed who had worked with open data projects that are funded in 2012 and in 2013. The study used a grounded theory approach that begins its analysis by coding the qualitative data obtained via semi-structured interviews of 16 project managers who worked with Vinnova-funded open data projects, and then these codes are used as input for correspondence analysis.
This research showed that, to understand impact of government funded projects, homogeneity among projects and organizations should be considered. Due to Vinnova’s heterogeneous selection of funded projects and organizations, not all public or private organizations showed similar correlation at the correspondence analysis. In addition to that, some organizations are registered as private organization but funded by public authorities where they represent a mix of public and private organizations character. Nevertheless, results revealed that, in general, public organizations are usually associated to no interest to business/business models, structure and standardization of datasets and visibility of datasets. Private organizations, on the other hand, are more associated to business models, content of data, demand for data and value of the data. This study underlines main concerns during open data projects in regard to creation of value from open data projects.