CCRP MISSION STATEMENT

The Colouring Cities Research Programme (CCRP) is an academic research programme run at the Alan Turing Institute (UK), designed to support the development of open data platforms about the building stock, and to promote and advance reproducible, ethical and collaborative data science. The key research question posed by the programme is as follows:

Can open-source platforms providing open data on the composition, performance and dynamics of building stocks, able to test diverse methods of geospatial data capture and visualisation and actively engage built environment stakeholders in their development and maintenance, be cost-effectively set up and managed by research institutions, to effect a step-change in the amount and quality of data on stocks available for integration, synthesis, dissemination, and analysis, necessary to support their sustainable and resilient development at global level?

The CCRP's main research goals can be summarised as follows: To produce permanent networked platforms that:

• Release open geospatial data on building stock, of a type, format and quality able to support research into the improvement of the sustainability, resilience, quality and efficiency of the building stock and the United Nation's New Urban Agenda;
• Release open data able to improve understanding of the stock as a dynamic system - its composition, performance and quality, and dynamic behaviour;
• Release data of a scale and quality able to support the use of AI and machine learning in data analysis, simulation and forecasting;
• Maximise accessibility for all stakeholders;
• Increase opportunities for open knowledge sharing about stocks, and collaborative research between diverse stakeholders at national and international level;
• Increase opportunities for integrating diverse geospatial data capture methods and testing feedback loops between these;
• Promote openness, inclusivity, trustworthiness in data science, and drive up ethical standards relating to building attribute data and its application;
• Generate open-source code able to be easily reproduced across countries to support the efficient sharing of data, skills and knowledge to support global sustainability goals;
• Are sufficiently adaptable to provide open national databases, which combined provide data on the global stock, able to be built-on in perpetuity;
• Reduce inefficiency in academia, maximise opportunities for researchers, and increase public understanding of the importance of academic research in meeting UN Sustainabale Development Goals.