Visualization Laboratory.

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In this laboratory, we conduct research to realize the development of “Interactive Data Analysis and Visualization (Data Analysis and Visualization: DAV)” technology to promote scientific discoveries using data obtained from various phenomena through measurements and calculations, as well as the social implementations for such technology.

   So what do we mean by scientific discovery?

Scientific discovery does not necessarily mean major discoveries at a Nobel Prize level. In this laboratory, we believe that scientific discoveries can be obtained through research activities using scientific methods. Here, the scientific method consists of components such as observing phenomena of interest, setting a problem for the phenomena of interest, building a hypothesis around the problem, verifying the constructed hypothesis, and socially implementing the verified hypothesis.

Among these, the hypotheses playing an important role in scientific discoveries are often constructed as causal relationships. In many cases, a causal relationship is often described in the form of “if XX(cause), then YY (result),” and it is possible to manipulate the hypothesis (convert it into a computable format) and associate data with it.

The activities in this laboratory correspond to each component of the scientific method.

For observations and problem setting of particular phenomena, these activities are related to the improvement and development of data generation technology related to the phenomena. Measurement and calculation techniques for data generation are being developed in the field of natural sciences, but this is not necessarily the case in the humanities or social sciences.

In addition, we will also improve and develop data visualization techniques for looking through the generated data as a whole at the phenomena observation and problem setting stage.

Regarding hypothesis construction and verification, we will improve and develop data analysis techniques to support the search for causal relationships from different data. In addition, we will also improve and develop data visualization and interactive operation techniques for specifying the time and space where causal relationships are established.

In the social implementation stage of the verified hypothesis, it is necessary to improve and develop techniques for creating awareness of the hypothesis in the target field. In addition, this laboratory will gather the latest results on data analysis, such as causal relationship search techniques, and promote the utilization of these results according to their context.

Comprehensive Visualization

  1. Particle Volume Rendering
  2. Graph Drawing

Causal Relationship Visualization

  1. Elucidation of Developmental Dynamics in Nematodes
  2. Social Implementation of Climate Change Adaptation Measures
  3. Construction of Brain Function Network
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Comprehensive Visualization

Causal Relationship Visualization