Gerson Galang

The Australia urban research gateway

The

Towards an e-Infrastructure for Urban Research across Australia

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

A data-driven urban research environment for Australia

Many challenges facing urban and built environment researchers stem from the complexity and diversity of the urban data landscape. This landscape is typified by multiple independent organizations each holding a variety of heterogeneous data sets of relevance to the urban community. Furthermore, urban research itself is diverse and multi-faceted covering areas as disparate as health, population demographics, logistics, energy and water usage, through to socio-economic indicators associated with communities. The Australian Urban Research Infrastructure Network (AURIN) project (www.aurin.org.au) is tasked with developing an e-Infrastructure through which a range of urban and built environment research areas will be supported. This will be achieved through development and support of a common (underpinning) e-Infrastructure. This paper outlines the requirements and design principles of the e-Infrastructure and how it aims to provide seamless, secure access to diverse, distributed data sets and tools of relevance to the urban research community. We also describe the initial case studies and their implementation that are currently shaping this e-Infrastructure.

Security Attribute Aggregation Models for E-research Collaborations

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.

Elastic Scaling of e-Infrastructures to Support Data-Intensive Research Collaborations

Supporting distributed, research collaborations is a fundamental demand of e-Research infrastructures (e-Infrastructures). To be successful, e-Infrastructures must address the needs of all parties involved including end user researchers and associated stakeholders, e.g. organizations that make resources available. These needs often translate into ensuring the security and integrity of systems and data sets used for research purposes. Whilst a cornerstone of e-Research has been to support single sign-on, i.e. where users are not required to provide multiple username/passwords, the reality is that most single sign-on solutions have been based around authentication-oriented only models based on public key infrastructures. For many researchers and organizations, finer-grained access control (authorization) is essential. Such authorization solutions typically depend on delivery of security attributes that determine the privileges of individuals that can subsequently be used to determine their access requests to organizational resources. In this paper we identify attribute delivery patterns that support different authorization-oriented collaborative models. These patterns are currently being explored within the context of the Australian Urban Research Infrastructure Network (AURIN -- www.aurin.org.au).

Privacy Preserving Geo-Linkage in the Big Urban Data Era

For many research endeavours, e-Infrastructures need to provide predictable, on-demand access to large-scale computational resources with high data availability. These need to scale with the research communities requirements and use. One example of such an e-Infrastructure is the Australian Urban Research Infrastructure Network (AURIN -- www.aurin.org.au) project, which supports Australia-wide research in and across the urban and built environment. This paper describes the architecture of the AURIN infrastructure and its support for access to distributed (federated) and highly heterogeneous data sets from a wide range of providers. We present how this architecture solution leverages the intersection of high throughput computing (HTC), infrastructure as a service (IaaS) Cloud services and big data technologies including use of NoSQL resources. The driving concept in this architecture and the focus of this paper is the ability for scaling up or down depending on resource demands at any given time. This is done automatically and on demand avoiding either under-or over-utilization of resources. This resource-optimization-driven infrastructure has been designed to ensure that peak loads can be predicted and successfully coped with, as well as avoid wasting resources during non-peak times. This overall management strategy has resulted in an e-Infrastructure that provides a flexible, evolving research environment that scales with research needs, rather than providing a rigid (static) end product.

Enabling SDMX-based Retrieval and Spatio-statistical Analysis of National Census and Related Datasets

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.

A lightweight authorization mechanism for spatially enabled health data services

This paper describes a collaborative project between the Australian Urban Research Infrastructure Network (AURIN), the Australian Bureau of Statistics (ABS), the University of Queensland eResearch Lab and a number of social science research centres across Australia - that provides programmatic access to ABS Census data sets to enable its re-use within a range of research projects. The project successfully demonstrates machine-to-machine access to 2011 Census data through a federated data hub model that dynamically delivers statistical datasets to the research community. Using an SDMX web services approach, combined with advanced data analytics and visualization services available through the AURIN workbench, social scientists are able to manipulate and visualize national census data overlaid with other related data sets through a sophisticated mapping interface. Integrated statistical analysis services (R-based) also enable social scientists to quantify correlations between different demographic and socio-economic parameters. A number of socio-economic use-cases are presented that illustrate how the system enables researchers to understand and quantify changes in industry sectors, labor force needs, employment, population needs and disadvantage, over space and time. The paper also outlines problems and limitations revealed through the demonstrator projects, lessons learnt and areas that will require further effort to deliver optimum access to national census data sets and associated e-social science infrastructure for both the Australian and global social science community.

Designing Adaptable Spatial Cyberinfrastructure for Urban eResearch

Ensuring that only authorized users have access to certain sensitive datasets is of paramount importance and this is especially so in the health sector. While the importance of the ability to access and utilize such data to better manage public health has been increasingly recognized, the process of defining and enforcing access management remains largely ad hoc with data provider specific solutions typically required. This is due to the heterogeneity of data and in situations where systems are already in place and are expected to remain so for a foreseeable future. In this context, we present a lightweight and data provider-driven software system for providing access to health records that include geospatial information. The proposed architecture is lightweight as it focuses on the re-use of existing data-access standards and services familiar to health data providers. The system is data provider-driven since it only allows access to and use of health data for research purposes through data provider initiated processes. The solution described has been designed in the context of the Australian Urban Research Infrastructure Network (AURIN) Project together with a (federated) data provider to extend the visibility and accessibility of their spatially enabled healthcare database.

The design of a flexible web-based analytical platform for urban research

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.