Visualization of Superficial Similarities between Data Jackets for Aiding Creativity on Innovators Marketsplace on Data Jackets

In recent years, various data has been obtained at different situations due to the improvement of the sensors or the popularization of the Internet and mobile phones. In the field of business, academia or politics, the demand for supporting decision making based on data has been increased. Ohsawa et al. propose the concept of the market of data (MoDAT) for the demand, and provide Innovators Marketplace on Data Jackets (IMDJ) as a method for realizing MoDAT, which is a workshop method for encouraging particippants to utilize and exchange data. However, although participants of the workshop discuss the given theme each other, possible combinations of DJs for satisfying requirements are hardly generated. That is one of the problems of IMDJ. In this paper, in order to solve the problem, we propose the visualization method for representing the similarities between DJs using latent dirichlet allocation (LDA) and multidimensional scaling (MDS) in order to aid users metacognition in IMDJ. The result shows that our proposed method improve the performance of participants to create feasible solutions by combining DJs. (C) 2016 Published by Elsevier B.V.