Members of SMART’s research team have been involved in two successful grant applications made to the Australian Research Council (ARC).
The two projects, Urban Analytics Data Structure and Enhanced modelling capacity for the Industrial Ecology Virtual Laboratory, have been granted $805,000 and $260,000 respectively as part of ARC’s Linkage Infrastructure, Equipment and Facilities (LIEF) funding scheme.
This scheme provides funding for research infrastructure, equipment and facilities to eligible organisations. It is aimed at enabling higher education researchers to participate in cooperative initiatives so that expensive infrastructure, equipment and facilities can be shared between higher education organisations and also with industry.
“ARC’s delivery of this funding is reflective of the calibre of the facility’s research team, and their ongoing commitment to collaborating on projects significant on both a domestic and international scale,” commented Professor Chris Cook, Executive Dean of University of Wollongong’s Faculty of Engineering and Information Sciences (EIS).
“These major and competitive grants emphasise SMART’s position at the forefront of innovative and impactful infrastructure research,” Prof. Cook continued.
Professor Pascal Perez, the recently appointed, Director of SMART Infrastructure Facility (SMART), is listed alongside Dr Rohan Wickramasuriya, SMART Visiting Associate (Research Fellow), as Chief Investigators on the Urban Analytics Data Structure project. According to the funding application, this project aims to:
“develop an Urban Analytics Data Infrastructure that explicitly leverages and builds on the Australian Urban Research Infrastructure Network (AURIN). This digital data infrastructure intends to enable the integration, harmonisation, connectivity and scalability of multi-source urban datasets. These capabilities are predicated on the adoption of ISO standards, the development of new ontological frameworks and an urban data dictionary to enable semantic inferencing of datasets, and the development of 3D/4D data structures and services. This fundamental framework will then be applied to urban data relevant to people, land and urban infrastructure to support new capacities in comparative and multi-dimensional analytics.”
Prof. Perez’s role on this project will involve leading the implementation of the fundamental technical framework for water and energy use and service quantity and quality, in residential and other land uses, and per capita water and sanitation supply service, consumption, wastewater collection and treatment, and develop the open API and necessary supporting web services (supported by Dr Wickramasuriya). He will supervise the project staff based at UOW.
Dr Wickramasuriya will work collaboratively with other members of the project team to lead the development of web-based semantic-inferencing services to support automated integration (including metadata).
In addition to his role as Chief Investigator on Urban Analytics Data Structure, Prof. Perez will also act as a Chief Investigator for the other project, Enhanced modelling capacity for the Industrial Ecology Virtual Laboratory. The aim of this project is to:
“enable Australian research leaders working on the integrated assessment of policies, products and projects concerning economy and environment to collaborate in the Industrial Ecology Virtual Laboratory (IELab). It will develop and implement an enhanced modelling capability and a suite of online analytical tools to support sustainability scientists and analysts from Australia and abroad conducting research projects of national and international significance. By upgrading IELab hardware and analytical and modelling software, the project will implement a maximum level of continuous updating, versatility and flexibility to ensure policy relevance and global leadership of new research for many years.”
On this project, Prof. Perez’s role will be to manage and coordinate the development of the IO-econometric module within the IELab. This module will allow for IO-based simulations that track shifts in the economic structure due to demographic and various other exogenous changes.