Building an e-infrastructure to support urban and built environment research in Australia: a Lens-centric view

Transcription

1 Proceedings of the SURVEYING & SPATIAL SCIENCES CONFERENCE 2013 April 2013 Canberra Australia Building an e-infrastructure to support urban and built environment research in Australia: a Lens-centric view Christopher Pettit 1, Robert Stimson 1 Martin Tomko 1, Richard Sinnott 2, 1 The University of Melbourne, Faculty of Architecture Building and Planning, Melbourne, Australia 2 The University of Melbourne, Faculty of Engineering, Melbourne, Australia cpettit@unimelb.edu.au ABSTRACT The Australian Urban and Research Infrastructure Network (AURIN) is a $20 million Education Infrastructure Funding (EIF) initiative that is building an e-infrastructure to support the urban research and built environment research community across Australia. AURIN is tasked with building an e-infrastructure that provides seamless access to relevant (distributed) data, with integrated analysis and presentation tools incorporating mapping and visualisation capabilities. The project is undertaking a bottom-up approach whereby the user community (urban and built environment researchers) are determining what datasets should be incorporated and the associated e-research tools required to access and interrogate this data to support both discipline specific and interdisciplinary research endeavours. For the purposes of the AURIN project, the urban and built environment research community has been organised into Lenses strategic implementation streams covering population demographics, health, transport and others. These Lenses are represented by panels of domain experts from across the country. Many of these Lenses cut across data, tools and comprise expertise stemming from the university, government and private sectors. The aim of this paper is to introduce this Lens-centric approach for determining requirements for datasets and e-research tools. We introduce the AURIN open source portal and enabling technical architecture and describe how this is being built to support the Australian urban and built environment research community. We introduce some of the key datasets that are coming into the AURIN research environment, how these have been driven by Lens requirements and implemented through available web-based solutions. We also introduce the data and metadata management systems that have been developed and illustrate some of the data interrogation and visualisation tools currently available. We identify some of the strengths and challenges in building a user driven e-infrastructure and the lessons learnt so far in building this e-infrastructure. KEYWORDS: urban and built environment research, e-infrastructure, open source, visualisation, datasets, e- Research tools.

2 1 INTRODUCTION The Australian Urban Research Infrastructure Network (AURIN) has been tasked by the Commonwealth Government of Australia to deliver an e-infrastructure to support the urban and built environment research community in addressing issues of national significance. The aim of AURIN is to build a state of the art online workbench, which provides merit based access to a wide range of data holdings and e-research tools to support data interrogation and visualisation to inform better planning and design of our cities and urban fabric. AURIN was conceived with two main components: the strategic implementation streams, known as Lenses, and the supporting technical architecture required to support and integrate the Lenses and so demonstrate the potential to current and future urban and built environment researchers in Australia. This paper focuses on the role of the Lenses in determining the end user priorities both from a data and e-research tool perspective in building the AURIN e-infrastructure. We first introduce the AURIN les and describe their role and rationale for their selection. We provide a detailed discussion on one of the Lenses urban housing, to illustrate the Lens-centric approach in defining data requirements and e-research tools. We then introduce the AURIN technical architecture and the existing workbench, accessible through the AURIN portal, to provide a flavour of the type of system being developed to handle the end user requirements specified through the Lenses. We conclude the paper by discussing some of the strengths and challenges in this Lens-centric approach for building an e-infrastructure to support urban and built environment researchers across Australia. 2 THE LENS-CENTRIC APPROACH AURIN was conceived with a number of strategic implementation streams, referred to as Lenses, which relate to issues of national significance. The Lenses initially selected aimed to address some of the key challenges facing Australia s diverse urban system. They reflect issues of national concern as outlined in key government documents that set the agenda for priorities around cities and the built environment (COAG, 2009; Major Cities Unit, 2010). The role of the Lenses was to focus on key areas of urban research and enumerate the data types and research methodology approaches and requirements of the AURIN research e-infrastructure to support data access, interrogation and visualisation (AURIN EIF Final Project Plan, 2011). A number of principles were established to govern how the Lenses would be implemented. These included: 1. Focus on achieving a demonstrator effect, illustrating what is possible by opening up data access and making available e-research tools. 2. Avoid the fragmentation of the use of e-infrastructure into small scale and specialised activities that do not support the longer term goal of the AURIN e- infrastructure to facilitate better access to data and e-research tools to enhance urban and build environment research across Australia. 3. Minimise the generation of large volumes of new data, rather focus in on targeted investments in providing access to largely extant data and product and services that

3 maybe be derived from them. 4. Data and e-research tools need to be driven by wider community-of-interest rather than individual researcher-based interests. Lens Expert Groups have been established to guide the design and implementation of each Lens. The Expert Groups comprise national leaders across academia, government and the private sector whose task it is to identify priority data requirements, e-research tools and components that should be implemented in AURIN. It has been anticipated that each Lens will vary in terms of scale, coverage and complexity, and in accordance with pragmatic considerations concerning the difficulties of accessing the required data. For example, it may be possible for the datasets to be incorporated into the e-infrastructure for a Lens to be fully national in coverage at say the level of scale of Statistical Local Areas (SLAs). Alternatively, for demonstration purposes it may be decided to focus attention on the implementation of a Lens to one or two metropolitan cities for a number of reasons. An exemplar city might be selected due to available co-investment from participating agencies and the provision of data in order to demonstrate the application of specific data interrogation tools to enable important hypotheses to be tested or for simulations to be run through the enabling e-research capabilities provided in the AURIN e-infrastructure (AURIN EIF Final Project Plan, 2011). The initial 10 aspirational Lenses identified in the AURIN EIF Final Project Plan (2011) ( which cater for a significant range of interests amongst Australia s diverse urban and built research community are as follows: 1. Population and demographic futures and benchmarked social indicators, 2. Economic activity and urban labour markets; 3. Urban health, well-being and quality of life; 4. Urban housing; 5. Urban transport; 6. Energy and water supply and consumption; 7. City logistics; 8. Urban vulnerability and risks; 9. Urban governance, policy and management; and 10. Innovative urban design. It was anticipated that work on the Lenses would be undertaken in a sequential order and the experiences in implementing the earlier Lenses would determine whether all Lenses would be embarked on through the life of the AURIN I work program. Lenses 1, 2 and 3 are currently well underway with the Expert Groups established and operational. Through a series of meetings the Expert Groups for these Lenses have identified investment priorities which has led to the funding of a number of data and e-research tool related projects as outlined in Table 1. Lenses 4, 5,and 6 are also currently underway with Expert Groups established and a number of sub-contracted projects being finalised with development expected to commence in early 2013.

4 Table 1. Funded AURIN sub-contract projects in Lens 1,2 and 3. S = Scoping Study, D = Dataset, E = e-research Tool. Lens Project title Lead Institute Sub-State Demographic Projections: Methods University of Queensland's Centre 1 and Data Access - scoping study for Population Research (QCPR) University of Canberra's National Centre Small area social indicators for the Indigenous for Social and Economic Modelling 1 population (NATSEM) University of Canberra's National Centre for Social and Economic Modelling 1 NATSEM small area wellbeing & quality of life Analytical tools for the interrogation of 1 inter regional migration flows matrices OECD Benchmarked Social and Economic Indicators Provision of infrastructure and data integration for Functional Economic Regions e-research tools to generate economic spatial statistics and conduct regional impact analysis 2 Input Output Tables for Australia National dataset and infrastructure provision 2 (NDIP) for AURIN Urban Health Geovisualisation e-research 3 Tool Development and trial of an automated open 3 source walkability tool Characterizing networks in geographical and social space integrating tools for network 3 analysis North Metropolitan Region of Melbourne Data Access Integration and Interrogation and 3 Demonstrator Projects Spatial Objective Contextual Data An Analytical Platform for the Integration of VicHealth Indicators Survey and Spatial 3 Objective Data Access to service Indicator City of 3 Melbourne (NATSEM) University of Queensland's Centre for Population Research (QCPR) University of Adelaide's Australian Population and Migration Research Centre (APMRC) University of Newcastle's Centre of Full Employment and Equity (CofFEE) University of Newcastle's Centre of Full Employment and Equity (CofFEE) University of Adelaide's Australian Workplace Innovation and Social Research Centre (WISeR) University of Adelaide's Public Health Information Development Unit (PHIDU) Collaborative Research Centre for Spatial Information University of Melbourne's McCaughey Centre University of Melbourne's Melbourne School of Population Health University of Melbourne's Centre for Spatial Data Infrastructure and Land Administration (CSDILA) RMIT University's School of Business IT and Logistics Melbourne City Research, Melbourne City Council Project Type S D D E D D E E D E E E D & E D & E D & E The number of AURIN sub-contracted projects is expected to be between through the life of the AURIN work program, which is due for completion mid Consequently, the AURIN management board has made the decision to cut down what can be implemented in the initial set of 10 aspirational Lenses. Therefore, Lenses 7 and 8 will not progress as stand alone Lenses within the context of the existing AURIN work program. Lens 9 will be scaled back and implementation will occur in the context of Lenses 1,2 and

5 3. Lens 10 - Urban Design - has been considered a priority and the Expert Group has been formed and scoping of priority datasets and e-research tools is currently underway. The next section of the paper provides further detailed analysis of one of the strategic implementation streams, Lens 4 - Urban Housing. This provides an exemplar and insight into how the Lens-centric approach is undertaken to define priority datasets and e- Research tools which are required to meet the broader needs of the urban and built environment research community in Australia. 2.1 Urban Housing Lens The supply, demand and access to housing are major public policy concerns in Australia. Housing plays a central role in driving key urban investment decisions and in framing behavioural outcomes across Australia s metropolitan cities and its regional cities and towns. The availability, affordability, location and quality of housing underpin many other aspects of urban life, patterns of mobility and employment, infrastructure, services, education and health (AURIN EIF Final Project Plan; 2011). Access to a cadastre-linked data (i.e. data linked at the address level) and a nationally consistent dataset on property prices was identified in the AURIN Investment Plan (2010) as a priority to support urban and built environment researchers who wished to provide answers to questions such as: Where is affordable housing located? What role do regional housing markets play in meeting housing need? Are private rental markets responding to shocks at the local scale - such as the impact of major mining developments? What is the spatial distribution of government assistance and property taxation outcomes? In late 2011 the AURIN Lens 4 Urban Housing Expert Group met for the first time with the aim to provide direction on specific data and e-research tool priorities and to identify what demonstrator projects should be established along with their situational context. One of the first tasks for the Expert Group was to define an operational framework and the situational context for the Urban Housing Lens. A systems thinking approach (Ackoff, 1974) was used to map the urban housing system in Australia including the high-level inputs, outputs and boundaries comprising the urban housing system see Figure 1. In determining the situational context for the AURIN Housing Lens the Expert Group concluded that at least a component of Lens 4 be implemented to provide national urban coverage, particularly for data that is spatially aggregated and can be provided for levels of geography commensurate with aggregated national-coverage data that will be provided through other AURIN Lenses. The Expert Group concurred that the development of demonstrator projects using highly disaggregated data (cadastre level or below) and their integration and interrogation to address issues of policy significance would be a worthwhile endeavour for the Urban Housing Lens. Both Sydney and Melbourne were identified as priority situational contexts for that purpose because of the complexity and diversity of their housing markets and in order to take advantage of the extensive existing effort that exists in those cities in relation to assembling datasets and their integration, especially through the work arising through the research centres of the Australian Housing Urban Research Institute (AHURI). The focus on the demonstrators were to 3 key areas: (1) Housing affordability, (2) Housing Supply, and (3) Housing and land use growth patterns.

6 Figure 1. Operational Framework for AURIN Housing Lens Over the duration of four meetings the Expert Group continued to refine the data and e- Research tool priorities. Table 2 provides an indicative list of the key datasets that would benefit those researchers interested in urban housing issues across Australia. Such datasets are expected to be of interest to urban and built environment researchers who have an interest in other areas covered by other AURIN Lens. By opening up such datasets it is envisaged that interdisciplinary research can occur to deal with the complex urban system and planning for sustainable urban form and settlement patterns. Table 2 Key Datasets identified by Urban Housing Expert Group Data Description Custodian Level of Aggregation Residential property and land valuation data Valuer General Land parcel Property description including: GFA, Number of Valuer General Land parcel bedrooms and bathrooms Property Classification Code (4 levels) Valuer General Land parcel Cadastral land boundary and area Public Sector Mapping Land parcel Agency (PSMA) Building Footprints Local Council Sub land parcel Building Height Local Council Sub land parcel Property Rating Systems. e.g. BASIX in NSW State Housing and Land parcel Public housing waiting lists State Housing and Individual

7 Public housing tenure State Housing and Development approval and information on type of State Housing and dwelling Land release State Housing and Land parcel Zoning State Housing and Land parcel Population projections State Housing and Census SLA / SA2 Housing authority data including public housing State Housing and waiting lists Rental bond data State Housing and Commonwealth rent assistance & first home owner State Housing and grant (FHOG) Homelessness data Australian Institute of Health and Wealth Small Area Statistics census (2011, 2006, 2001 ) Australian Bureau of Statistics (ABS) Population migration data ABS Census SLA / SA 2 Financial data on housing not sure if available ABS SLA / SA2 Residential dwellings approvals data ABS Census SLA / SA2 Estimated household income ABS Census SLA / SA2 Survey of income and housing renters and buyers ABS Individual Land accounts ABS SLA / SA2 Census household sample Confidentialised 120,000 records (1% sample) Finance data on housing debt and loans data. Not sure if available Mortgage finance data (equity data) Not sure if available Supply of investment housing based on tax returns on depreciation schedules Not sure if available National Exposure Information Systems (NEXIS) data including: age profile, replacement of building costs, construction cost of building value in reconstruction terms, insurance data Household, Income and Labour Dynamics in Australia (HILDA) Survey ABS Reserve Bank of Australia (RBA) RBA Australian Tax Office (ATO) Geosciences Australia Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) Land parcel, census SLA/ SA2 Land parcel Land parcel, Census SLA / SA2 Land parcel, Census SLA / SA2 Land parcel, Census/ SLA / SA2 Individual, SLA / SA2 Census CD / Mesh block / SLA / SA 1 / SA 2 Individual SLA / SA2 SLA / SA2 SLA / SA2 Census SLA / SA2 Individual Rental housing payments data FaHCSIA Census SLA / SA2 Benefits data Centrelink Census SLA / SA2 Housing / Mortgage Stress Ontario International National Centre for Census SLA / SA2 Benchmark Social and Economic Modelling (NATSEM) Housing Affordability Index NATSEM Census SLA / SA2 Total housing Demand (total sales and total rentals NATSEM Census SLA / SA2 per month) Housing Rental Private Sector Land Parcel, Census SLA/SA2 Housing Sales Private Sector Land Parcel

8 The Expert Group has also considered the key generic suite of e-research tools that will be needed as part of the AURIN e-infrastructure for researchers to interrogate, analyse and visualise data relevant to urban housing. In the context of the AURIN e-infrastructure there is a requirement that these tools be developed online and in open source as part of the workbench to support urban and built environment researchers. Specifically for urban housing researchers there is a need for a suite of e-research tools that can support spatial and statistical analysis, computer simulation modelling and for visualisation of data at a level of the Australian Bureau of Statistics (ABS) census geography and also at the land parcel level. Both spatial and temporal analysis needs to be supported through the AURIN e-research toolkit. The priority list of e-research tools to support the Urban Housing Lens as identified by the Expert Group include: 1. Basic data search, discovery and download tools to provide urban housing researchers access to a wide range of datasets via the AURIN portal. 2. Urban housing decision support dashboard tool to support exploration of data and scenarios. 3. Land use modelling and simulation tools such as What if? (Klosterman, 1998) and SLEUTH (Clarke et al., 1997). 4. Demographic and economic driven urban growth models and implications for new dwelling construction such as the SEQ Large Scale Urban Model (LSUM) (Stimson et al.,2012). 5. Analytic tools for visualizing flow data (e.g. population migration). 6. A neural network based house price forecasting model. 7. New rental housing models. 8. Hedonic pricing modelling tools. 9. Vacancy rate models a vacancy rate index for cities (synthetic data created). 10. An automated workflow, which runs a series of algorithms for developing indicators. For example, developing a housing shortage index based on spatial factors. An example of one of the e-research tools which the Expert Group has identified, and that is now being implemented within the AURIN e-infrastructure, is the Online What if? (OWI) Pettit et al., in press). OWI is a conversion of the desktop What if GIS based collaborative planning support system developed by Klosterman (1999) into an online open source component to the AURIN workbench. OWI supports planners and decision-makers in exploring alternative future land use change scenarios. The e-research tool calculates land supply parameters based on multiple criteria, which can then be used to create land suitability scenarios as illustrated in Figure 2. Land use demand is calculated through factors such as population projections, household size and household structure. OWI comprises a land use allocation module, which generates future land use simulations, known as what-if scenarios. OWI is a collaborative planning support tool, which requires a number of datasets identified in Table 2 in order to generate land use suitability, demand and allocation scenarios. The value of unlocking such datasets as outlined in Table 2 to support urban and built environment research is critical if advanced computer modelling and simulation tools such as OWI are to be made available to support the planning and design of sustainable cities.

9 Figure 2. Online What if? Planning Support System for exploring future land use change scenarios (Pettit et al. in Press) 3 BUILDING A WORKBENCH TO SUPPORT URBAN AND BUILT ENVIRONMENT RESEARCH The AURIN technical architecture (Figure 3) has been designed by the core AURIN technical team within the University of Melbourne eresearch Group. In developing this infrastructure, it has been recognised that there is a need for the technical architecture to evolve so that it can adapt to handle new forms of data and to accommodate new needs within the Lenses that might arise in the existing or future AURIN work program. For example, OWI is developed as an e-research tool within the AURIN workbench and needs to be accommodated into the technical architecture accordingly, as highlighted in Figure 4. The AURIN workbench itself is being implemented through a joint effort by both the core technical team and externally contracted groups. For example, the AURIN metadata entry tool has been developed by the Centre for Spatial Data Infrastructure and Land Administration (CDILA), building upon the open source Geonetwork platform and their previous work in developing an automated metadata tool (see Olfat et al 2012, Olfat et al. 2010). All datasets need to be registered within the Spatial Metadata Tool illustrated in Figure 4 to be searchable and usable within the AURIN e-infrastructure. Whilst, the Spatial Metadata Tool is not tightly integrated within the AURIN service based architecture it is an important component of the AURIN workbench. Further details of the AURIN metadata system will be published in a subsequent research paper.

10 Figure 3 Overview of the AURIN Service based architecture (Sinnott et al. 2012) Figure 4 Spatial Metadata Tool for AURIN Portal Example Screenshot To meet the needs of the Lenses the AURIN workbench needs to be user driven and satisfy the needs of the urban and built environment research community as represented through the AURIN Lenses. Figure 5 illustrates the AURIN end user flow support (Tomko et al. 2012), which is data driven. The Expert Groups have resoundingly highlighted the importance of a data driven approach and the need to access a disparate array of datasets to undertake both deep discipline and also interdisciplinary research. The necessity to download data where possible to enable researchers to run their own analysis has been identified in the AURIN Final project plan (2011) and further identified as a priority by the Urban Housing and other AURIN Expert Groups. Subsequently, when a researcher accesses the AURIN e-infrastructure they are given the option of entering the portal for

11 shopping, analysing and visualising data, or simply being able to download data see Figure 6. Figure 5 AURIN End user flow support (Tomko et al. 2012) Figure 6 Urban and built environment researchers can choose between accessing AURIN Portal or secure data download The workbench incorporates a number of visualisation tools and techniques that have been identified as important for end users to explore and analyse AURIN datasets. A summary of the key visualisation techniques relevant to AURIN is outlined in Pettit et al. (2012). In summary these include (i) graphs and charts, (ii) Choropleth mapping see Figure 7 for example, (iii) heat mapping (iv) flow mapping, (v) brushing, (see Figure 7), (vi) space time cube (STC) representation and (vii) Decision Support Dashboards. AURIN is also considering 3D volumetric visualisation capability as part of its workbench and the Urban Design Lens 10 will guide the requirements of such functionality.

12 Figure 7 Choropleth mapping and brushing functionality available through the AURIN workbench. 4 STRENGTHS AND CHALLENGES OF THE LENS CENTRIC APPROACH The AURIN project to date has identified a number of strengths and challenges in undertaking a Lens-centric approach for defining end user requirements and developing the workbench. A Lens-centric approach has provided a formal structure for the urban and built environment research community to identify data and e-research tool priorities. The Lenses represent various sections of the research community and through the establishment of Expert Groups those particular datasets and e-research tools of importance to a particular research community, for example urban housing, can be readily identified. It is the Lens-centric approach that empowers the end user community as they are directly engaged in defining the e-infrastructure requirements. The AURIN stakeholder group is 500 individuals and growing, which is encouraging and an indicator of the level of engagement and expectation on what the e-infrastructure can deliver. This level of end user expectation, whilst considered a strength is in fact a challenge for AURIN. With a finite set of resources (both time and money), there is a limit to how many datasets can be made available to end users and the number of e-research tools that can coded and supported via the AURIN workbench. The decision to develop the workbench using open source software also results in strengths and challenges to AURIN. The strengths being that open source software typically mitigates software licensing costs and also the code is contributed back to the research community to develop further. The challenges with this approach is that it requires significant software development experience to build- e-research tools and in many cases the existing software and code might not be as mature and hardened as that available in proprietary software packages. Another key challenge relating to the Lenses is to prevent them becoming self-contained silos of data and tools servicing the needs of a small subset of the urban and built environment research community. Initially the AURIN technical architecture was conceived such that each Lens was understood as a Virtual Organisation (VO) and would have its

13 own specific requirement on the realisation of data and services (AURIN EIF Final Project Plan, 2011). However, experience in the project and feedback from the Lens Expert Groups has suggested that end users should have access to a suite of datasets and tools that cut across Lens streams and therefore the e-infrastructure should not be implemented in a way that segregates the urban and built environment research community via a number of Lens specific VOs. For example, an urban transport researcher should be able to access and shop for urban health and urban housing data and interrogate and visualise these disparate datasets via the AURIN workbench to undertake interdisciplinary research. These are but some of the key strengths and challenges which have been identified to date. As the project continues to develop there will be further experiences and lessons learnt that will be reported in further research and development papers. 5 CONCLUSION In this paper we have introduced a Lens-centric approach for building an e-infrastructure to support urban and built environment research in Australia. This Lens-centric approach has a number of benefits including that Lenses: (i) provide an aspirational set of areas of national significance to focus on, (ii) are driven by the collective intelligence of expert groups, (iii) provide a direct connection to end users - urban and built environment researchers, (iv) Identify opportunities for co-investment and collaboration, (v) provide a mechanism for building national capability and prioritisation of data and e-research tool required by the end user community. The Lenses act as selective views, within which the data collation and the design of the infrastructure can be framed, developed and quality assured. They provide a framework for goals and potential research scenarios by which to shape and test the infrastructure design and implementation (AURIN EIF Final Project Plan, 2011). Experiences to date on the project highlight the strengths of the Lens-centric approach in identifying the focus for sub-contracted projects and areas of collaboration. However, this has resulted in the identification of between sub-project contracted pieces of work to date, which will prove a challenge in terms of project management and technical integration (Sinnott et al. 2013). One of the major lessons learned from identifying and implementing the first suite of AURIN sub-contract projects, as identified in Table 1, is that different levels of data and technical maturity exists across Australia. This is most apparent in dealing with data and open source software. Various datasets are maintained to different levels of sophistication and the adoption of open data standards and protocols for data collection differs greatly between data communities. A data and technical maturity model which articulates the current state of play of key datasets and e-research tools critical to the urban and built environment research is currently being developed by AURIN which will be a valuable resource. Finally, the concept of data hubs is emerging as way of identifying the core federated data infrastructure required to support a truly nationally networked e- infrastructure. Both the data and technical maturity model and data hubs concepts will be explored and reported in future research.

14 6 ACKNOWLEDGEMENTS The authors would like to acknowledge the support of the AURIN Lens Expert Groups and committees that are shaping the direction and implementation of AURIN. The AURIN project is funded through the Australian Education Investment Fund Super Science Initiative made possible through the Australian Government - Department of Industry, Innovation Science, Research and Tertiary Education. REFERENCES Ackoff, R. L Redesigning the Future: A Systems Approach to Societal Problems. John Wiley & Sons, Chichester, UK. AURIN EIF Final Project Plan (2011), April (available on AURIN Investment Plan (2010),June (available on Clarke, K. C, Gaydos, L., and Hoppen, S. (1997) A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B 24: COAG, The Council of Australian Government s Meeting, Brisbane, December 2009, Communique. Klosterman, R. E. (1999) The What if? Collaborative Planning Support System. Environment and Planning, B: Planning and Design 26: Major Cities Unit, 2010, State of Australian Cities, Commonwealth of Australia, Major Cities Unit, Infrastructure Australia, Canberra. Olfat, H. Kalantari, M. Abbas Rajabifard, A Williamson, I. (2012) Towards a foundation for spatial metadata automation, Journal of Spatial Science Vol. 57, 1,pp Olfat, H., Kalantari, M., Rajabifard, A., Williamson, I.P., Pettit, C. and Williams, S. (2010) Exploring the key areas of spatial metadata automation research in Australia. In proceedings of GSDI 12 World Conference: Realising Spatially Enabled Societies, Singapore, October. Pettit, C.J. Klosterman, R.E. Nino-Ruiz, M. Widjaja, I., Tomko, M., Sinnott, R. Stimson, R. (in press). The Online What if? Planning Support System in Planning Support Systems for Sustainable Urban Development, Eds Geertman, S and Stillwell, J. Springer Publishers. Pettit, C. Widjaja, I, Russo, P, Sinnott, R, Stimson, R, Tomko, M. (2012) Visualisation support for exploring urban space and place, XXII ISPRS Congress, Technical Commission IV 25 August 01 September 2012, Melbourne, Australia Editor(s): M. Shortis, J. Shi, E. Guilbert, ISPRS Annals Vol 1-2, pp Sinnott, R.O, Bayliss, C, Morandini, L, Tomko, M. (2013) Tools and Processes to Support the Development of a National Platform for Urban Research: Lessons (Being) Learnt from the AURIN Project, Australasian Computer Science Week, Jan 29-Feb 1st, Adelaide, South Australia. Sinnott, R.O., Bayliss, C., Galang, G., Greenwood, P., Koetsier, G., Mannix, D., Morandini, L., Nino-Ruiz, M., Pettit, C., Tomko, M. (2012), A Data-driven Urban Research Environment for Australia, The 8th IEEE International Conference on escience (escience 2012), Chicago, Illinois, 8-12 October 2012.

15 Stimson, R., Bell, M., Corcoran, J. and Pullar, D. (2012), Using a large scale urban model to test planning scenarios in the Brisbane-South East Queensland region, Regional Science Policy and Practice, 4, pp Tomko, M., Bayliss, C. Widjaja, I., Greenwood, P., Galang, G., Koetsier, G., Sarwar, M., Nino-Ruiz, M., Mannix, D., Morandini, L., Voorsluys, W., Pettit, C., Stimson, R., and Sinnott, R. (2012) The Design of a Flexible Web-based Analytical Platform for Urban Research, 20th ACM SIGSPATIAL, Redondo Beach, California, November 6-9th. Tomko, M., Galang, G.G., Bayliss, C., Koetsier, J., Greenwood, P., Voorsluys, W., Mannix, D., Sarwar, M., Widjaja, I., Pettit, C., and Sinnott, R. (2013, in review). Designing Adaptable Spatial Cyberinfrastructures - the example of a Loosely-Coupled Internal System Architecture for Urban eresearch In CyberGIS: Fostering a New Wave of Geospatial Discovery and Innovation, S. Wang and M. Goodchild Eds. Springer Verlag.