The Data Analytics for Urban Transformations (DAUT) cluster addresses research about and with data analytics at the intersection of social sciences, exact sciences, and data sciences. Our cluster applies and advances evolving techniques, such as AI/ML, time-based methods, and comparative approaches to investigate complex urban challenges.
The DAUT cluster is composed of IHS research staff members interested in developing and applying data analytics methods within urban contexts. To cope with the increasing complexity of urban challenges, trans- and interdisciplinary approaches are required, asking for tailored and advanced analytical methods. Positioned at the intersection of social sciences, exact sciences, and data sciences, the cluster responds to a context where powerful tools and rapidly evolving techniques (including machine learning, process- and time-based methods, and comparative approaches) are readily accessible. The cluster is highly diversified with experts from various disciplines, including physical sciences, economics, sociology, planning, and engineering. By learning from each other’s analytical expertise and skills, we push the boundaries of traditional urban data analytics, incorporating novel modeling approaches to uncover challenges in urban transformations. With the DAUT cluster, we establish and strengthen partnerships with a variety of organisations including universities and local governments worldwide.
