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Advanced Research Computing

Future Cities

Today, advanced computational systems control our cities infrastructures and provide tools to test future human-designed environments. 

To understand this computationally intensive environment, iARC is exploring new dimensions and initiatives that cut across scales from global human-made infrastructure and materials, down to micro individual atoms that monitor and track movement. 

This theme aims to help motivate a research agenda for Future Cities computing, including mitigated, conceptual and technical challenges in using various GIS software.

Key areas of complexity include the representation, computation and visualisation of data, as well as the integration of spatial and temporal data that is around cities.

In recent years a growing number of research projects undertaken by scholars are computationally geographic in the sense of particularly concerning place, or having geospatial analysis as a principle methodology. Naturally this has led to the use of software such as GIS software for both mapping and analysis as well as the theoretical understanding of the range and spread of cities.

  • Air Conditioning
  • Construction
  • Energy Efficiency

Future Cities relate to geographical information systems in a general sense, but are not limited to such large packages and inclusive of an active open-source informational ecosystem within which Digital Humanities scholars are becoming more prevalent. Elements of this system include software for web mapping and analysis in programming languages (Javascript, Python and R) and geospatial linked data.

Topic and themes that are of interest to iARC include, but are not limited to:

  • Infrastructure and architecture
  • landscape modelling
  • Mobility
  • Modeling multivocality: “open-world” assumption in “closed-world” systems
  • Modelling, encoding, and computing over uncertain, sparse, or indeterminate spatial and temporal data 
  • Semantic computing: linked data, ontologies and simulation
  • Urban design and planning
  • Visualisation of uncertainty in maps and associated timelines