Understanding and enhancing research-policy linkages in Australian housing: A discussion paper

This project aimed to develop a systematic framework for understanding the relationship between social science research and public policy, and to build more effective linkages between social researchers and policy practitioners in the Australian housing system, particularly through AHURI. The project is explicitly applied and solution-focused. It was undertaken in close collaboration with AHURI and has contributed to AHURI's overall mission and strategy to enhancing research-based housing policy. It provided an opportunity for the AHURI policy community to engage in a process of action-oriented, self-reflection around its core business of applied housing policy research.

Regional investment strategies (RIS) and coastal catchment initiative (CCI) project alignmnet to Great Barrier Reef Water Quality Protection Plan

The Great Barrier Reef Water Quality Protection Plan (the Reef Plan) is a joint initiative of the Australian and Queensland Governments. The Reef Plan aims to progress an integrated approach to natural resource management planning by building on the existing partnerships between the different levels of government, industry groups, the community and research providers within the Reef catchments, principally through partnerships with the regional natural resource management (NRM) bodies.

The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.