Transdisciplinary Research

Data science is an interdisciplinary field. Many of the existing and future data science problems are complex, and the complexity will require a transdisciplinary approach to address.

Instead of individual disciplines coming up with their own solutions independently, multiple disciplines must come together to recognize the problem first, and then devise solutions that are only possible when multiple disciplines work together to design that one solution. For example, the many problems of an ageing population can benefit from taking a transdisciplinary approach, one that includes colleagues from Engineering, Computing, Medicine, Public Health, Arts and Social Science pushing ahead in data science research in concert and with a clear purpose.

As the focal point for university-wide data science research, the value of the solutions that the Institute can provide is through bringing together experts from multiple Schools and Faculties to investigate a problem from multifaceted perspectives. The Institute will coordinate data science research and funding for developing integrated capabilities, leverage on and mobilize existing strengths in NUS to collectively address real-life data science problems.