Integrating data-driven decision-support, energy models and data analytics in urban transition governance

The digitalisation of cities creates a wealth of data which can be of great support for governing the urban energy transition.

Decisions on infrastructure investments, energy planning, or measures to change behaviour can be improved by urban data analytics and energy modelling. However, using such data resources is no straightforward process.

Not only are data sources often proprietary, distributed and sensitive from a privacy perspective, but the models and decision-support tools are often driven more by technical considerations than by the needs and usability for different types of decision-makers in cities.

This interdisciplinary collaboration of an engineering and a social science PhD student will deal with the development of participatory modelling tools and their embedding in organisational processes and energy decision making.

The aim is to use urban data in a more reflective and needs-oriented way to enable informed decisions in the transition to climate-neutral cities.