A systematic framework for the complex system engineering of city data governance

The importance of data governance in the information age has become a deep consensus among all sectors. Under this context, data-driven urban governance has also become a key requirement for city development. However, as smart city and digital government continuously make progress, the utilization of urban data is still far from true intelligence, and no theoretical research on city data governance can fully guide the concrete implementation of engineering practice. In view of this, this paper proposes a systematic framework for the complex system engineering of urban data governance. We deconstruct urban data governance into a series of basic elements and discuss the key problems in urban data governance engineering regarding three dimensions, i.e., data quality, value and security. In view of the complexity of engineering projects, we establish the systematic framework of urban data governance from four levels, i.e., cognitive, methodological, technical and practical, and demonstrated the application in real practice with a case study on data-based epidemic prevention and control project in Shenzhen. The framework is proposed aiming to break through the key common difficulties in the practice of urban data governance engineering, provide systematic and operable solutions, and finally achieve the set goals.