Interdisciplinary Communication for Risk Management with Multi-Data Mining

E4 Chair: Mikhail Zgurovsky

F4 Chair: Yukio Ohsawa

G4 Chair: Yukio Ohsawa

A number of urgent problems are rising to human life:  The attack of terrorists is hard to predict, due to the hidden leaderships. New diseases are hard to extinguish, due to their new causes. Products should be improved, due to the appearance of new desire of users. A common feature to these socially high-impact problems is that they are open to multiple scientific domains. For example, the source body of a causal virus of SARS is still unclear. For solving this problem, we require the collaboration of across medical science, food science, ecological science, zoology, and the analysis of data from these scientific domains. This track is made of session series aiming at developing a data-based aiding methods and methodologies for interdisciplinary creative communication about an emerging social problem. The core problems are:

- What is the understandable representation of knowledge for non-experts of a certain data set?

- How can an expert talk to a non-expert about his/her discovery?

- How can participants of interdisciplinary discussion share common vocabulary?

- How can the participants achieve a consensus, in spite of working in different domains and on different expertise?

- Can machine work for discovering patterns and creating knowledge understandable for non-experts of the target data ?

- What are the new applications to be realized by solving these questions?