Today, there is an urgent need to shorten the time and reduce the cost of materials development. In addition to traditional experimental and computational approaches, new data-driven materials development approaches that extract valuable information and knowledge attract attention. The goal of materials research and development using data science approaches is to quantitatively evaluate the accuracy and uncertainty of results derived from existing data, reduce the number of costly experiments in the search for new materials, and efficiently propose composition combinations and fabrication conditions. To achieve this goal, we focus on developing fundamental and applied technologies of data science adapted to materials science to effectively analyze and utilize measured and computed big data in materials science.
