Semantic Visualization Support for Innovators Marketplace on Data Jackets

Following the trend of big data, the business value of data is becoming a hot research field in recent years. The novel concept of Data Jacket introduced by Ohsawa et al. solved the difficult problem of data transactions due to the particular characteristic of data, i.e. the safeguarding privacy. In order to make sure the mechanism of the market of data, there are some researchers proposed a gamified workshop to simulate the real data transactions terms Innovators Marketplace on Data Jackets. But the problem is that in the workshop, participants can hardly combine useful data jackets to consider valuable solutions. In order to motivate participants to propose reasonable solutions helping for data transactions, this paper proposes a new visualization method to cluster data jackets by semantic similarity applying word mover's distance (WMD) and multidimensional scaling (MDS), and to verify the hypothesis whether solutions from combining different domains of data jackets are more valuable. The result shows the feasibility of this visualization method which can help providing valuable solutions by questionnaire.