Ivo Widjaja

The Australia urban research gateway

The

The Online What if? Planning Support System

20m Australian Urban Research Infrastructure Network (AURIN) project (www.aurin.org.au) began in July 2010. AURIN has been tasked with developing a secure, Web‐based virtual environment (e‐Infrastructure) offering seamless, secure access to diverse, distributed and extremely heterogeneous data sets from numerous agencies with an extensive portfolio of targeted analytical and visualization tools. This is being provisioned for Australia‐wide urban and built environment researchers – itself a highly heterogeneous collection of research communities with diverse demands, through a unified urban research gateway. This paper describes these demands and how the e‐Infrastructure and gateway is being designed and implemented to accommodate this diversity of requirements, both from the user/researcher perspective and from the data provider perspective. The scaling of the infrastructure is presented and the way in which it copes with the spectrum of big data challenges (volume, veracity, variability and velocity) and associated big data analytics. The utility of the e‐Infrastructure is also demonstrated through a range of scenarios illustrating and reflecting the interdisciplinary urban research now possible. Copyright

Identifying painters from color profiles of skin patches in painting images

The chapter introduces the Online What if? (OWI) GIS-based planning support system, which is being made available through the Australian Urban Research Infrastructure Network (AURIN). AURIN has been established to provide an advanced information infrastructure to support discipline-specific and multi-disciplinary research and promote sustainable urban development in Australia. OWI is an open source online version of the widely used desktop What if? planning support system developed by Klosterman (1999). OWI enables a range of end users to create and explore what if? land use change scenarios. This chapter discusses OWI in the context of a demonstrator case study in Hervey Bay, Queensland, and introduces future applications of this collaborative planning tool to support the sustainable planning of cities in Australia.

A data-driven urban research environment for Australia

Research on digital analysis of painting images has received very little attention. The exact nature of scientific methods seems to be antithesis of art. Nevertheless, several papers have proposed methods to bridge this gap and have obtained interesting results. In fact, some art theorists have pointed out the usefulness of specific quantifiable features in the paintings. This paper presents a method for identifying painters using color profiles of skin patches in painting images. Various color models for representing the color profiles were explored. Various implementations of multiclass support vector machine classfiiers were compared. We found that a weighted combination of several directed acyclic graph SVMs with Gaussian kernels gives the best classification performance.

Modeling coordinated multiple views of heterogeneous data cubes for urban visual analytics

The Australian Urban Research Infrastructure Network (AURIN) project (www.aurin.org.au) is tasked with developing an e-Infrastructure to support urban and built environment research across Australia. As identified in [1], this e-Infrastructure must provide seamless access to highly distributed and heterogeneous data sets from multiple organisations with accompanying analytical and visualization capabilities. The project is tasked with delivering a secure, web-based unifying environment offering a one-stop-shop for Australia-wide urban and built environment research. This paper describes the architectural design and implementation of the AURIN data-driven e-Infrastructure, where data is not just a passive entity that is accessed and used as a consequence of research demand, but is instead, directly shaping the computational access, processing and intelligent utilization possibilities. This is demonstrated in a situational context.

Embodied and enacted: the Janus faces of structure-of-use

With the explosion of digital data, the need for advanced visual analytics, including coordinated multiple views (CMV), is rapidly increasing. CMV enable users to discover patterns and examine relationships across multiple visualizations of one or multiple datasets. CMV have been implemented in a web-based environment through the Australian Urban Research Infrastructure Network (AURIN) project. AURIN offers a platform providing seamless and secure access to an extensive range of distributed urban datasets across Australia. Visual exploration of these datasets is essential to support research endeavors. This paper focuses on the challenges in dealing with complexity and multidimensionality of datasets used in CMV. We rely on the concept of multidimensional data cubes as the theoretical framework for coordination across visualizations. Using the concept of data cubes and hierarchical dimensions, we present strategies to automatically build render groups. This provides an implicit coordination based on cube structures and a framework to establish links between a dataset with its aggregates in a one-to-many fashion. The CMV approach is demonstrated using aggregate-level data, which is provided through federated data services. The paper discusses the issues around our CMV implementation and concludes by reflecting on the challenges in supporting spatio-temporal urban data exploration.

Privacy Preserving Geo-Linkage in the Big Urban Data Era

In this paper, we introduce two sides of structure pertinent to the design and use of an artifact: embodied structure and enacted structure. We then locate these concepts in both historical and contemporary examples: the game of chess, the development of the rule of the road, and the implementation of an information technology artifact within a particular organization. The significance of our attempt is two fold. Firstly, it provides an alternative analytical view in examining the structures within interaction between an artifact and its users. Secondly, it calls for consideration of these two structures when designing an artifact.

Designing Adaptable Spatial Cyberinfrastructure for Urban eResearch

Big data technologies and a range of Government open data initiatives provide the basis for discovering new insights into cities; how they are planned, how they managed and the day-to-day challenges they face in health, transport and changing population profiles. The Australian Urban Research Infrastructure Network (AURIN – www.aurin.org.au) project is one example of such a big data initiative that is currently running across Australia. AURIN provides a single gateway providing online (live) programmatic access to over 2000 data sets from over 70 major and typically definitive data-driven organizations across federal and State government, across industry and across academia. However whilst open (public) data is useful to bring data-driven intelligence to cities, more often than not, it is the data that is not-publicly accessible that is essential to understand city challenges and needs. Such sensitive (unit-level) data has unique requirements on access and usage to meet the privacy and confidentiality demands of the associated organizations. In this paper we highlight a novel geo-privacy supporting solution implemented as part of the AURIN project that provides seamless and secure access to individual (unit-level) data from the Department of Health in Victoria. We illustrate this solution across a range of typical city challenges in localized contexts around Melbourne. We show how unit level data can be combined with other data in a privacy-protecting manner. Unlike other secure data access and usage solutions that have been developed/deployed, the AURIN solution allows any researcher to access and use the data in a manner that meets all of the associated privacy and confidentiality concerns, without obliging them to obtain ethical approval or any other hurdles that are normally put in place on access to and use of sensitive data. This provides a paradigm shift in secure access to sensitive data with geospatial content.

VISUALISATION SUPPORT FOR EXPLORING URBAN SPACE AND PLACE

In this chapter, we present and discuss an adaptable cyberinfrastructure (e-Infrastructure) for urban research. We illustrate the benefits of a loosely coupled service-oriented architecture-based design pattern for the internal architecture of this e-Infrastructure. This is presented in the context of the Australian Urban Research Infrastructure Network (AURIN), which provides an urban research environment across Australia supporting access to large amounts of highly distributed and heterogeneous data with accompanying analytical tools. The system is being reactively designed based on evolving and growing requirements from the community. We discuss the differences between more common spatial data infrastructures (SDIs) and eResearch infrastructures, and describe the unique AURIN environment set up to provide these additional features. The different aspects of loose coupling in internal architectures are examined in the context of the implemented components of the AURIN system. We conclude by discussing the benefits as well as challenges of this system architecture pattern for meeting the needs of urban researchers.