Data is ubiquitous in our cities. However, designing a knowledge  network about our cities is an arduous task, given that data sensed cannot be used directly, human significance must be added. Adding human significance can be achieved via an automated “expert system (ES)” in which domain expert knowledge are stored in a knowledge-based repository. The domain expert knowledge is matched with the corresponding data to derive specific inference which can aid decision making for urban stakeholders. This requires amalgamation of various interdisciplinary techniques. This paper presents a survey of existing technologies in order to investigate the emerging issues surrounding the design of a live knowledge network for sustainable urban living. The maps and models of the existing infrastructure of our cities that include a wealth of information such as topography, layout, zoning, land use, transportation networks, public facilities, and resource network grids need to be integrated with real-time spatiotemporal information about the city. Public data in forms of archives and data streams as well as online data from the social network and the Web can be analyzed using data mining techniques. The domain experts need to interpret the results of data mining into knowledge that will augment the existing knowledge base and models of our cities. In addition to the analysis of archived and streamed data sources from the built environment, the emerging state-of-the-art Web 2.0 and mobile technologies are presented as the potential techniques to crowddesign a live urban knowledge network. Data modelling, data mining, crowdsourcing, and social intervention techniques are reviewed in this paper with examples from the related work and our own experiments.