Project

Generic library of spatial concepts and asset definitions  


Host university

Collaborating University

QUT

INDUSTRY PARTNERS

THEME ALIGNMENT

Spatial Data Infrastructures, Digital Twin and Decision Support

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INDUSTRY PROBLEM

Past and current practices in infrastructure and urban problem solving frequently challenged by siloed and contained ad-hoc solutions; ones that do not address root cause nor enable resilience across the urban infrastructure system. Domains and industries are composed of various levels of decision makers with their own codes and semantics around the data and systems in which they operate. Decision makers, data producers and users have separate lexicon for their data, processes and systems.  These arbitrary codes hold no meaning to those outside, and those without the language to understand their discipline specific meaning.  

As a result, data sharing and exchange are often blocked from realisation due to the sender and receiver not understanding the domain semantics  in order to aggregate and/or use data and greatly hamper the building and exploitation of Digital Twins. This is a linguistic, semantic and data knowledge problem; and it inhibits concurrent innovation maturity across connected systems. 


CONTACT CONTRIBUTORS

Sisi Zlatanova

RIIS Hub Lead Chief Investigator
University of New South Wales
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Johnson Xuesong Shen

Chief Investigator
UNSW Sydney
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Srinath Perera

Chief Investigator
Western Sydney University
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Jagannath Aryal

Chief Investigator
University of Melbourne
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Tommy Chan

RIIS Hub Lead Chief Investigator
Queensland University of Technology
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Graeme Kernich

Partner Investigator
FrontierSI
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