Review of the National Survey of Research Commercialisation (NSRC)

A review of the NSRC (the Review) is currently being undertaken to ensure future collections are relevant, align with current and emerging priorities for research commercialisation in Australia, are targeted to sector priorities and comparable with international data sources. Consideration of new metrics including options to introduce research/industry engagement measures will be included in the scope of the review. Australia’s publicly funded research community includes universities, publicly funded research agencies, medical research institutes and other research organisations. By international standards Australia performs well in terms of research excellence and output, but poorly in translating publicly funded research into commercial outcomes . A key reason for this is the insufficient transfer of knowledge between researchers and business. Australia ranks 29th and 30th out of 30 OECD countries on the proportion of large businesses and small to medium enterprises (SMEs) collaborating with higher education and public research institutions on innovation. The Australian Government is actively implementing policy incentives that will improve the translation of publicly funded research into commercial and broader public benefits. This includes 2014 budget measures such as the Entrepreneurs Infrastructure Programme and proposals announced as part of the Industry Innovation and Competitiveness Agenda and the Boosting the Commercial Returns from Research Discussion Paper . Consistent with the policy objective to improve research industry collaboration and commercialisation and thereby lift Australia’s productivity, prosperity and international competitiveness, the Government will refocus the NSRC. This includes capturing new and robust data that will provide a comprehensive picture of research commercialisation in Australia including pathways to commercialisation. &nbsp

Can urban metabolism models advance green infrastructure planning? Insights from ecosystem services research

Urban metabolism studies have gained momentum in recent years as a means to assess the environmental performance of cities and to point to more resource-efficient strategies for urban development. Recent literature reviews report a growing number of applications of the industrial ecology model for Material Flow Analysis (MFA) in the design of the built environment. However, MFA applications in green infrastructure development are scarce. In this article, we argue that: i) the use of MFA in green infrastructure practice can inform decision-making towards more resource-efficient urban planning; ii) the ecosystem service concept is critical to operationalize MFA for green infrastructure planning and design, and, through this, can enhance the impact of urban metabolism research on policy making and planning practice. The article draws from a systematic review of literature on urban ecosystem services and benefits provided by green infrastructure in urban regions. The review focuses on ecosystem services that can contribute to a more energy-efficient and less carbon-intensive urban metabolism. Using the Common International Classification of Ecosystem Services as a baseline, we then discuss opportunities for integrating energy provision and climate regulation ecosystem services in MFA. Our discussion demonstrates that the accounting of ecosystem services in MFA enables expressing impacts of green infrastructure on the urban energy mix (renewable energy provision), the magnitude of energy use (mitigation of building energy demand), and the dynamics of biogeochemical processes in cities (carbon sequestration). We finally propose an expanded model for MFA that illustrates a way forward to integrate the ecosystem service concept in urban metabolism models and to enable their application in green infrastructure planning and design

TICAL - a web-tool for multivariate image clustering and data topology preserving visualization

In life science research bioimaging is often used to study two kinds of features in a sample simultaneously: morphology and co-location of molecular components. While bioimaging technology is rapidly proposing and improving new multidimensional imaging platforms, bioimage informatics has to keep pace in order to develop algorithmic approaches to support biology experts in the complex task of data analysis. One particular problem is the availability and applicability of sophisticated image analysis algorithms via the web so different users can apply the same algorithms to their data (sometimes even to the same data to get the same results) and independently from her/his whereabouts and from the technical features of her/his computer. In this paper we describe TICAL, a visual data mining approach to multivariate microscopy analysis which can be applied fully through the web.We describe the algorithmic approach, the software concept and present results obtained for different example images