Cities are dynamic systems with multi-scaled dependencies. Yet, current practices of urban analytics, design, and usage are static and misaligned with the emerging life and virtualisation of the city, being in permanent flux. The emergence of big open urban data, knowledge graphs, Artificial Intelligence (AI), crowdsourcing methods, and the possibility of perpetually adjustable parameters demand a new mode of analysing, designing, and governing the city. The project asks how geo-data science, Semantic Web Technologies (SWT) applied to urban design and Computational Social Science approaches can be harnessed to achieve sustainable, resilient, and liveable cities.
This module has three interdependent and transdisciplinary work packages:
WP1: Integrated Urban Data Analysis builds on advances in geospatial technologies, in particular – data integration and geographic data science, and it incorporates AI techniques and novel streams of urban data.
WP2: Urban Design Ontologies builds on SWT allowing to link data across multiple knowledge domains and thus overcome major challenges in digitalisation of urban analysis and design such as data-interoperability, data search and knowledge inference, as well as scalability.
WP3: Smart Elements and Adaptable Infrastructures draws from the Computational Social Sciences to offer flexible uses of urban infrastructures freeing them from pre-described, static, mono-functional uses.
An urban element defines the archetypical characteristics and rules that describe how a piece of urban fabric ties together different aspects of the urban world into a functional whole. Such elements are typical features of the built environment that can range in scale from the texture of a pavement, a building entrance, a shop front, a plaza and street, or a neighbourhood. A Semantic Urban Element represents parts of the urban world as entities and relations in a machine-readable way. This leads to intelligible, scalable domain models instead of complex physical data models.
The project explores a potential paradigm shift in urban knowledge formation through urban big data analysis, near real-time computation in urban design, assessment and usage of smart urban elements across multiple urban domains as well as spatial and temporal scales.
