We accumulate case studies of data utilization research in collaboration with companies, governments, and local governments, and to build a “Data Science Casebank” for use in classes and graduation research.

FD活動による普及促進 ケースバンクを通して得られるフィードバックから 教育教材を補強(社会工学カリキュラム2.0)

It is said that we are living in a VUCA world. VUCA comes from the initial letters of volatility, uncertainty, complexity, and ambiguity. The feeling of unpredictability about the world is increasing, with the spread of COVID-19, frequent occurrence of torrential rain, international financial markets linked instantly, etc. In order to solve various complex intertwined social problems in a world where you cannot see ahead and have no compass, “social engineering” repeats the process of problem solving that involves: 1) understanding social phenomena in a scientific and engineering manner; 2) performing analysis using data; 3) designing better social systems, and if necessary; 4) performing tests and providing recommendations or; 5) conducting measurements and evaluations. Through our three majors, namely in Social and Economic Sciences, Management Science and Engineering, and Urban and Regional Planning, we aim to cultivate problem-solving data scientists proficient in specialist knowledge in the respective fields and having versatile knowledge of data science.

The “Data Science Casebank on Policy & Planning Sciences” project summarizes research undertaken at the College of Policy and Planning Sciences, which offers the above three majors, together with companies, central and local government, NPOs, and entities that drive society, to share the process of identification through the solution of problems. The issues in society and the entities working on them are varied, and even for the same problem, the ideal solution may differ depending on the group, such as an organization or a community. The road to a solution that can win the agreement of the stakeholders is found only through trial and error. The aim of the Casebank is to share information on what trial and error was carried out in the actual research, thereby providing hints for solving one's own research or business issues.

By utilizing this knowledge, including the latest data science in research and education, we aim to produce human resources capable of searching for and identifying diverse social problems from a multi-faceted perspective and boldly taking up the challenge of the frontiers of problem-solving, through which proposing better social systems.