Connecting people to their resource consumption through real-time data visualisations

Combining human-computer interaction and urban informatics, this design research developed and tested novel interfaces offering users real-time feedback on their paper and energy consumption. Findings from deploying these interfaces in both domestic and office environments in Australia, the UK, and Ireland, will innovate future generations of resource monitoring technologies. The study draws conclusions with implications for government policy, the energy industry, and sustainability researchers.

eHealth-as-a-Service (eHaaS) : a data-driven decision making approach in Australian context

A commitment in 2010 by the Australian Federal Government to spend $466.7 million dollars on the implementation of personally controlled electronic health records (PCEHR) heralded a shift to a more effective and safer patient centric eHealth system. However, deployment of the PCEHR has met with much criticism, emphasised by poor adoption rates over the first 12 months of operation. An indifferent response by the public and healthcare providers largely sceptical of its utility and safety speaks to the complex sociotechnical drivers and obstacles inherent in the embedding of large (national) scale eHealth projects. With government efforts to inflate consumer and practitioner engagement numbers giving rise to further consumer disillusionment, broader utilitarian opportunities available with the PCEHR are at risk. This paper discusses the implications of establishing the PCEHR as the cornerstone of a holistic eHealth strategy for the aggregation of longitudinal patient information. A viewpoint is offered that the real value in patient data lies not just in the collection of data but in the integration of this information into clinical processes within the framework of a commoditised data-driven approach. Consideration is given to the eHealth-as-a-Service (eHaaS) construct as a disruptive next step for co-ordinated individualised healthcare in the Australian context.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection I. Two-way quantitative data

Data associated with germplasm collections are typically large and multivariate with a considerable number of descriptors measured on each of many accessions. Pattern analysis methods of clustering and ordination have been identified as techniques for statistically evaluating the available diversity in germplasm data. While used in many studies, the approaches have not dealt explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions). To consider the application of these techniques to germplasm evaluation data, 11328 accessions of groundnut (Arachis hypogaea L) from the International Research Institute for the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the rainy and post-rainy growing seasons were used. The ordination technique of principal component analysis was used to reduce the dimensionality of the germplasm data. The identification of phenotypically similar groups of accessions within large scale data via the computationally intensive hierarchical clustering techniques was not feasible and non-hierarchical techniques had to be used. Finite mixture models that maximise the likelihood of an accession belonging to a cluster were used to cluster the accessions in this collection. The patterns of response for the different growing seasons were found to be highly correlated. However, in relating the results to passport and other characterisation and evaluation descriptors, the observed patterns did not appear to be related to taxonomy or any other well known characteristics of groundnut.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection. II. Two-way data with mixed data types

As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.

Taxonomic resolution and quantification of freshwater macroinvertebrate samples from an Australian dryland river : The benefits and costs of using species abundance data

In studies using macroinvertebrates as indicators for monitoring rivers and streams, species level identifications in comparison with lower resolution identifications can have greater information content and result in more reliable site classifications and better capacity to discriminate between sites, yet many such programmes identify specimens to the resolution of family rather than species. This is often because it is cheaper to obtain family level data than species level data. Choice of appropriate taxonomic resolution is a compromise between the cost of obtaining data at high taxonomic resolutions and the loss of information at lower resolutions. Optimum taxonomic resolution should be determined by the information required to address programme objectives. Costs saved in identifying macroinvertebrates to family level may not be justified if family level data can not give the answers required and expending the extra cost to obtain species level data may not be warranted if cheaper family level data retains sufficient information to meet objectives. We investigated the influence of taxonomic resolution and sample quantification (abundance vs. presence/absence) on the representation of aquatic macroinvertebrate species assemblage patterns and species richness estimates. The study was conducted in a physically harsh dryland river system (Condamine-Balonne River system, located in south-western Queensland, Australia), characterised by low macroinvertebrate diversity. Our 29 study sites covered a wide geographic range and a diversity of lotic conditions and this was reflected by differences between sites in macroinvertebrate assemblage composition and richness. The usefulness of expending the extra cost necessary to identify macroinvertebrates to species was quantified via the benefits this higher resolution data offered in its capacity to discriminate between sites and give accurate estimates of site species richness. We found that very little information (<6%) was lost by identifying taxa to family (or genus), as opposed to species, and that quantifying the abundance of taxa provided greater resolution for pattern interpretation than simply noting their presence/absence. Species richness was very well represented by genus, family and order richness, so that each of these could be used as surrogates of species richness if, for example, surveying to identify diversity hot-spots. It is suggested that sharing of common ecological responses among species within higher taxonomic units is the most plausible mechanism for the results. Based on a cost/benefit analysis, family level abundance data is recommended as the best resolution for resolving patterns in macroinvertebrate assemblages in this system. The relevance of these findings are discussed in the context of other low diversity, harsh, dryland river systems.

Mixed data types and the use of pattern analysis on the Australian groundnut germplasm data

Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

Twitter data analytics – or : the pleasures and perils of studying Twitter

It might still sound strange to dedicate an entire journal issue exclusively to a single internet platform. But it is not the company Twitter Inc. that draws our attention; this issue is not about a platform and its features and services. It is about its users and the ways in which they interact with one another via the platform, about the situations that motivate people to share their thoughts publicly, using Twitter as a means to reach out to one another. And it is about the digital traces people leave behind when interacting with Twitter, and most of all about the ways in which these traces – as a new type of research data – can also enable new types of research questions and insights.

Wet tropics reef rescue impact report 2009

The Wet Tropics region has a unique water asset and is also considered a priority region for the improvement of water quality entering the Great Barrier Reef due to a combination of high rainfall, intensive agricultural use, urban areas and the proximity of valuable reef assets to the coast. Agricultural activities are one of many identified threats to water quality and water flows in the Wet Tropics in terms of sediment and pollutant-related water quality decline. Information describing the current state of agricultural management practices across the region is patchy at best. Based on the best available information on agricultural management practices in the Wet Tropics in 2008, it is clear that opportunities exist to improve nutrient, sediment and pesticide management practice to reduce the impact on the water asset and the Great Barrier Reef. Based on current understandings of practices and the relationship between practices and reef water quality, the greatest opportunities for improved water quality are as follows: · nutrients – correct rate and the placement of fertilisers; · pesticides – improve weed control planning, herbicide rates and calibration practice; and · soil and sediment – implement new farming system practices. The 2008-09 Reef Rescue program sought to accelerate the rate of adoption of improved management practices and through Terrain invested $6.8M in the 2008-09 year for: · landholder water quality improvement incentive payments; · cross regional catchment repair of wetlands and riparian lands in areas of high sediment or nutrient loss; and · partnerships in the region to lever resources and support for on-ground practice change. The program delivered $3,021,999 in onground incentives to landholders in the Wet Tropics to improve farm practices from D or C level to B or A level. The landholder Water Quality Incentives Grants program received 300 individual applications for funding and funded 143 individual landholders to implement practice change across 36,098 ha of farm land. It is estimated that the Reef Rescue program facilitated practice change across 21% of the cane industry, and 20% of the banana industry. The program levered an additional $2,441,166 in landholder cash contributions and a further $907,653 in non-cash in-kind contributions bringing the total project value of the landholder grants program in the Wet Tropics to $6,370,819. Most funded projects targeted multiple water quality objectives with a focus on nutrient and sediment reduction. Of the 143 projects funded, 115 projects addressed nutrient management either as the primary focus or in combination with strategies that targeted other water quality objectives. Overall, 82 projects addressed two or more water quality targets. Forty-five percent of incentive funds were allocated to new farming system practices (direct drill legumes, zonal tillage equipment, permanent beds, min till planting equipment, GPS units, laser levelling), followed by 24% allocated to subsurface fertiliser applicators (subsurface application of fertiliser using a stool splitter or beside the stool, at the correct Six Easy Steps rate). As a result, Terrain estimates that the incentive grants achieved considerable reductions in nitrogen, phosphorus, sediment and pesticide loads. The program supported nutrient management training of 167 growers managing farms covering over 20% of the area harvested in 2008, and 18 industry advisors and resellers. This resulted in 115 growers (155 farms) developing nutrient management plans. The program also supported Integrated Weed Management training of 80 growers managing farms covering 8% of the area harvested in 2008, and 6 industry advisors and resellers. This report, which draws on the best available Reef Rescue Management Monitoring, Evaluation, Reporting, and Improvement (MERI) information to evaluate program performance and impact on water quality outcomes, is the first in a series of annual reports that will assess and evaluate the impact of the Reef Rescue program on agricultural practices and water quality outcomes. The assessment is predominantly focused on the cane industry because of data availability. In the next stage, efforts will expand to: · improve practice data for the banana and grazing industry; · gain a better understanding of the water quality trends and the factors influencing them in the Wet Tropics; in particular work will focus on linking the results of the Paddock to Reef monitoring program and practice change data to assess program impact; · enhance estimations of the impact of practice change on pollutant loads from agricultural land use; · gain a better understanding of the extent of ancillary practice (change not directly funded) resulting from Reef Rescue training/ education/communication programs; and · provide a better understanding of the economic cost of practice change across the Wet Tropics region. From an ecological perspective, water quality trends and the factors that may be contributing to change, require further investigation. There is a critical need to work towards an enhanced understanding of the link between catchment land management practice change and reef water quality, so that reduced nutrient, sediment, and pesticide discharge to the Great Barrier Reef can be quantified. This will also assist with future prioritisation of grants money to agricultural industries, catchments and sub catchments. From a social perspective, the program has delivered significant water quality benefits from landholder education and training. It is believed that these activities are giving landholders the information and tools to implement further lasting change in their production systems and in doing so, creating a change in attitude that is supportive and inclusive of Natural Resource Management (NRM). The program in the Wet Tropics has also considerably strengthened institutional partnerships for NRM, particularly between NRM and industry and extension organisations. As a result of the Reef Rescue program, all institutions are actively working together to collectively improve water quality. The Reef Rescue program is improving water quality entering the Great Barrier Reef Lagoon by catalysing substantial activity in the Wet Tropics region to improve land management practices and reduce the water quality impact of agricultural landscapes. The solid institutional partnerships between the regional body, industry, catchment and government organisations have been fundamental to the successful delivery of the landholder grant and catchment rehabilitation programs. Landholders have generally had a positive perception and reaction to the program, its intent, and the practical, focused nature of grant-based support. Demand in the program was extremely high in 2008-09 and is expected to increase in 2009-2010.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.

Metaphors of big data

Metaphors are a common instrument of human cognition, activated when seeking to make sense of novel and abstract phenomena. In this article we assess some of the values and assumptions encoded in the framing of the term big data, drawing on the framework of conceptual metaphor. We first discuss the terms data and big data and the meanings historically attached to them by different usage communities and then proceed with a discourse analysis of Internet news items about big data. We conclude by characterizing two recurrent framings of the concept: as a natural force to be controlled and as a resource to be consumed.

Monitoring spatiotemporal dynamics of human movement based on MAC address data

This thesis was a step forward in extracting valuable features from human's movement behaviour in terms of space utilisation based on Media-Access-Control data. This research offered a low-cost and less computational complexity approach compared to existing human's movement tracking methods. This research was successfully applied in QUT's Gardens Point campus and can be scaled to bigger environments and societies. Extractable information from human's movement by this approach can add a significant value to studying human's movement behaviour, enhancing future urban and interior design, improving crowd safety and evacuation plans.

Measuring the biases in self-reported disability status : Evidence from aggregate data

Self-reported health status measures are generally used to analyse Social Security Disability Insurance's (SSDI) application and award decisions as well as the relationship between its generosity and labour force participation. Due to endogeneity and measurement error, the use of self-reported health and disability indicators as explanatory variables in economic models is problematic. We employ county-level aggregate data, instrumental variables and spatial econometric techniques to analyse the determinants of variation in SSDI rates and explicitly account for the endogeneity and measurement error of the self-reported disability measure. Two surprising results are found. First, it is shown that measurement error is the dominating source of the bias and that the main source of measurement error is sampling error. Second, results suggest that there may be synergies for applying for SSDI when the disabled population is larger. © 2011 Taylor & Francis.

Integration of XML Schemas for the Exchange of FDOT Construction Project Data

An investigation of the construction data management needs of the Florida Department of Transportation (FDOT) with regard to XML standards including development of data dictionary and data mapping. The review of existing XML schemas indicated the need for development of specific XML schemas. XML schemas were developed for all FDOT construction data management processes. Additionally, data entry, approval and data retrieval applications were developed for payroll compliance reporting and pile quantity payment development.