文摘
The potential expectation about generating innovative businesses and creating values by combining data from different regions has been increased, however, even the information about data and knowledge of data utilization are not shared. In order to lead data-driven innovations, a market of data is expected to reduce the risks of data utilization, and encourage data exchange. Data Jacket (DJ) has been proposed as the technique for sharing the information about data by publishing the summary of datasets as meta-data. Even if the data itself is not open in public, DJs enable the stakeholders in the market of data to consider the latent value of datasets by understanding the information about data described on DJs. Datasets described in DJs have various sharing policies of data, such as Open Data from governments, or private data from companies or individuals. Although, in general, there is a preconception that “the fee-charging things are better than the free ones”, the relationship of sharing policies and the utility expectations of data has not discussed in the market of data. In this study, we examine which data is expected higher for utilizing, that is, comparing the utility expectation of the data which can be shared in public (Public Data) and the data which cannot be shared (Private Data). Observing the frequency of uses in Innovators Marketplace on Data Jackets, which is the gamified workshop for discussing the data utilization, and analyzing the number of views in DJ Store, which is the retrieval system of DJs, the result shows that the data which is hardly open may be recognized valuable for utilizing.