Collaborating to develop research data management services and collections

The Queensland University of Technology (QUT) Library, like many other academic and research institution libraries in Australia, has been collaborating with a range of academic and service provider partners to develop a range of research data management services and collections. Three main strategies are being employed and an overview of process, infrastructure, usage and benefits is provided of each of these service aspects. The development of processes and infrastructure to facilitate the strategic identification and management of QUT developed datasets has been a major focus. A number of Australian National Data Service (ANDS) sponsored projects - including Seeding the Commons; Metadata Hub / Store; Data Capture and Gold Standard Record Exemplars have / will provide QUT with a data registry system, linkages to storage, processes for identifying and describing datasets, and a degree of academic awareness. QUT supports open access and has established a culture for making its research outputs available via the QUT ePrints institutional repository. Incorporating open access research datasets into the library collections is an equally important aspect of facilitating the adoption of data-centric eresearch methods. Some datasets are available commercially, and the library has collaborated with QUT researchers, in the QUT Business School especially strongly, to identify and procure a rapidly growing range of financial datasets to support research. The library undertakes licensing and uses the Library Resource Allocation to pay for the subscriptions. It is a new area of collection development for with much to be learned. The final strategy discussed is the library acting as “data broker”. QUT Library has been working with researchers to identify these datasets and undertake the licensing, payment and access as a centrally supported service on behalf of researchers.

Factors influencing funding decisions by elected politicians at the state/provincial level : a case study of public libraries in Canada

The purpose of this study was to determine factors (internal and external) that influenced Canadian provincial (state) politicians when making funding decisions about public libraries. Using the case study methodology, Canadian provincial/state level funding for public libraries in the 2009-10 fiscal year was examined. After reviewing funding levels across the country, three jurisdictions were chosen for the case: British Columbia's budget revealed dramatically decreased funding, Alberta's budget showed dramatically increased funding, and Ontario's budget was unchanged from the previous year. The primary source of data for the case was a series of semi-structured interviews with elected officials and senior bureaucrats from the three jurisdictions. An examination of primary and secondary documents was also undertaken to help set the political and economic context as well as to provide triangulation for the case interviews. The data were analysed to determine whether Cialdini's theory of influence (2001) and specifically any of the six tactics of influence (i.e, commitment and consistency, authority, liking, social proof, scarcity and reciprocity) were instrumental in these budget processes. Findings show the principles of "authority", "consistency and commitment" and "liking" were relevant, and that "liking" were especially important to these decisions. When these decision makers were considering funding for public libraries, they most often used three distinct lenses: the consistency lens (what are my values? what would my party do?), the authority lens (is someone with hierarchical power telling me to do this? are the requests legitimate?), and most importantly, the liking lens (how much do I like and know about the requester?). These findings are consistent with Cialdini's theory, which suggests the quality of some relationships is one of six factors that can most influence a decision maker. The small number of prior research studies exploring the reasons for increases or decreases in public library funding allocation decisions have given little insight into the factors that motivate those politicians involved in the process and the variables that contribute to these decisions. No prior studies have examined the construct of influence in decision making about funding for Canadian public libraries at any level of government. Additionally, no prior studies have examined the construct of influence in decision making within the context of Canadian provincial politics. While many public libraries are facing difficult decisions in the face of uncertain funding futures, the ability of the sector to obtain favourable responses to requests for increases may require a less simplistic approach than previously thought. The ability to create meaningful connections with individuals in many communities and across all levels of government should be emphasised as a key factor in influencing funding decisions.

The big data upgrade : new dimensions in data analysis - risks and opportunities [das big data upgrade : neue dimensionen der datennutzung – chancen und risiken]

Summary: More than ever before contemporary societies are characterised by the huge amounts of data being transferred. Authorities, companies, academia and other stakeholders refer to Big Data when discussing the importance of large and complex datasets and developing possible solutions for their use. Big Data promises to be the next frontier of innovation for institutions and individuals, yet it also offers possibilities to predict and influence human behaviour with ever-greater precision

Multi-criteria ranking and source apportionment of airborne particulate matter

Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

Informed use of patients' records on trusted health care services

Health care is an information-intensive business. Sharing information in health care processes is a smart use of data enabling informed decision-making whilst ensuring. the privacy and security of patient information. To achieve this, we propose data encryption techniques embedded Information Accountability Framework (IAF) that establishes transitions of the technological concept, thus enabling understanding of shared responsibility, accessibility, and efficient cost effective informed decisions between health care professionals and patients. The IAF results reveal possibilities of efficient informed medical decision making and minimisation of medical errors. Of achieving this will require significant cultural changes and research synergies to ensure the sustainability, acceptability and durability of the IAF

How to Improve Cardiac Surgery Decision Making? In Data Warehousing Perspective

The health system is one sector dealing with very large amount of complex data. Many healthcare organisations struggle to utilise these volumes of health data effectively and efficiently. Therefore, there is a need for very effective system to capture, collate and distribute this health data. There are number of technologies have been identified to integrate data from different sources. Data warehousing is one technology can be used to manage clinical data in the healthcare. This paper addresses how data warehousing assist to improve cardiac surgery decision making. This research used the cardiac surgery unit at the Prince Charles Hospital (TPCH) as the case study. In order to deal with other units efficiently, it is important to integrate disparate data to a single point interrogation. We propose implementing a data warehouse for the cardiac surgery unit at TPCH. The data warehouse prototype developed using SAS enterprise data integration studio 4.2 and data was analysed using SAS enterprise edition 4.3. This improves access to integrated clinical and financial data with, improved framing of data to the clinical context, giving potentially better informed decision making for both improved management and patient care.

Over time assessment data analysis tracking a school's on-going performance

In Australia, as in some other western nations, governments impose accountability measures on educational institutions (Earl, 2005). One such accountability measure is the National Assessment Program - Literacy and Numeracy (NAPLAN) from which high-stakes assessment data is generated. In this article, a practical method of data analysis known as the Over Time Assessment Data Analysis (OTADA) is offered as an analytical process by which schools can monitor their current and over time performances. This analysis developed by the author, is currently used extensively in schools throughout Queensland. By Analysing in this way, teachers, and in particular principals, can obtain a quick and insightful performance overview. For those seeking to track the achievements and progress of year level cohorts, the OTADA should be considered.

A longitudinal study of grieving in family caregivers of people with dementia

A longitudinal study of grieving in family caregivers of people with dementia Recent research into dementia has identified the long term impact that the role of care giving for a relative with dementia has on family members This is largely due to the cognitive decline that characterises dementia and the losses that can be directly attributed to this. These losses include loss of memories, relationships and intimacy, and are often ambiguous so that the grief that accompanies them is commonly not recognised or acknowledged. The role and impact of pre-death or anticipatory grief has not previously been widely considered as a factor influencing health and well-being of family caregivers. Studies of grief in caregivers of a relative with dementia have concluded that grief is one of the greatest barriers to care giving and is a primary determinant of caregiver well-being. The accumulation of losses, in conjunction with experiences unique to dementia care giving, place family caregivers at risk of complicated grief. This occurs when integration of the death does not take place following bereavement and has been associated with a range of negative health outcomes. The aim of this research was to determine the influence of grief, in addition to other factors representing both positive and negative aspects of the role, on the health related quality of life of family caregivers of people with dementia, prior to and following the death of their relative with dementia. An exploratory research project underpinned by a conceptual framework of caregivers’ adaptation in the context of subjective appraisal of the strains and gains in their role was undertaken. The research comprised three studies. Study 1 was a scoping study that involved a series of semi-structured interviews with thirteen participants who were family caregivers of people with severe dementia or whose relative with dementia had died in the previous twelve months. The results of this study in conjunction with factors identified in the literature informed data collection for the further studies. Study 2 was a cross sectional survey of fifty caregivers recruited when their relative was in the moderate to severe stage of dementia. This study provided the baseline data for Study 3, a prospective cohort follow up study. Study 3 consisted of seventeen participants followed up at two time points after the death of their relative with dementia: six weeks and then six months following the death of the relative with dementia. The scoping study indicated that differences in appraisal of the care giving role and encounters with health professionals were related to levels of grief of caregivers prior to and following the death of the relative with dementia. This was supported in the baseline and follow up studies. In the baseline study, after adjusting for all variables in multivariate regression models, subjective appraisal of burden was found to make a significant contribution (p<.05) to mental health related quality of life. The two dependent variables, anticipatory grief and mental health related quality of life, were significantly (p<.01) correlated at a bivariate level. In the follow up study, linear mixed modelling and multiple regression analysis of data found that subjective appraisal of burden and resilience were significantly associated (p<.05 and p<.01, respectively) with mental health related quality of life over time. In addition, bereavement and complicated grief were significantly associated (p<.05) with mental health following the death of the relative. In this study social support and satisfaction with end of life care were found to be statistically associated (p<.05) with physical health related quality of life over time. The strong relationship between grief of caregivers and their health related quality of life over the entire care giving trajectory and period following the death of their relative highlights the urgent need for further research and interventions in this area. Overall results indicate that addressing the risk and protective factors including subjective appraisal of their care giving role, resilience, social support and satisfaction with end of life care of their relative, has the potential to both ameliorate negative health outcomes and to promote improved health for these caregivers. This research provides important information for development of targeted and appropriate interventions that aim to promote resilience and reduce the personal burden on caregivers of people with dementia.

Energy efficient virtual machine placement in data centers

Electricity cost has become a major expense for running data centers and server consolidation using virtualization technology has been used as an important technology to improve the energy efficiency of data centers. In this research, a genetic algorithm and a simulation-annealing algorithm are proposed for the static virtual machine placement problem that considers the energy consumption in both the servers and the communication network, and a trading algorithm is proposed for dynamic virtual machine placement. Experimental results have shown that the proposed methods are more energy efficient than existing solutions.

Alternative models of cardiac rehabilitation : a systematic review

The traditional hospital-based model of cardiac rehabilitation faces substantial challenges, such as cost and accessibility. These challenges have led to the development of alternative models of cardiac rehabilitation in recent years. The aim of this study was to identify and critique evidence for the effectiveness of these alternative models. A total of 22 databases were searched to identify quantitative studies or systematic reviews of quantitative studies regarding the effectiveness of alternative models of cardiac rehabilitation. Included studies were appraised using a Critical Appraisal Skills Programme tool and the National Health and Medical Research Council's designations for Level of Evidence. The 83 included articles described interventions in the following broad categories of alternative models of care: multifactorial individualized telehealth, internet based, telehealth focused on exercise, telehealth focused on recovery, community- or home-based, and complementary therapies. Multifactorial individualized telehealth and community- or home-based cardiac rehabilitation are effective alternative models of cardiac rehabilitation, as they have produced similar reductions in cardiovascular disease risk factors compared with hospital-based programmes. While further research is required to address the paucity of data available regarding the effectiveness of alternative models of cardiac rehabilitation in rural, remote, and culturally and linguistically diverse populations, our review indicates there is no need to rely on hospital-based strategies alone to deliver effective cardiac rehabilitation. Local healthcare systems should strive to integrate alternative models of cardiac rehabilitation, such as brief telehealth interventions tailored to individual's risk factor profiles as well as community- or home-based programmes, in order to ensure there are choices available for patients that best fit their needs, risk factor profile, and preferences.

A data mining driven risk profiling method for road asset management

Road surface skid resistance has been shown to have a strong relationship to road crash risk, however, applying the current method of using investigatory levels to identify crash prone roads is problematic as they may fail in identifying risky roads outside of the norm. The proposed method analyses a complex and formerly impenetrable volume of data from roads and crashes using data mining. This method rapidly identifies roads with elevated crash-rate, potentially due to skid resistance deficit, for investigation. A hypothetical skid resistance/crash risk curve is developed for each road segment, driven by the model deployed in a novel regression tree extrapolation method. The method potentially solves the problem of missing skid resistance values which occurs during network-wide crash analysis, and allows risk assessment of the major proportion of roads without skid resistance values.

A data mining framework for relevance feature discovery

This thesis is a study for automatic discovery of text features for describing user information needs. It presents an innovative data-mining approach that discovers useful knowledge from both relevance and non-relevance feedback information. The proposed approach can largely reduce noises in discovered patterns and significantly improve the performance of text mining systems. This study provides a promising method for the study of Data Mining and Web Intelligence.

Recognising team activities from noisy data

Recently, vision-based systems have been deployed in professional sports to track the ball and players to enhance analysis of matches. Due to their unobtrusive nature, vision-based approaches are preferred to wearable sensors (e.g. GPS or RFID sensors) as it does not require players or balls to be instrumented prior to matches. Unfortunately, in continuous team sports where players need to be tracked continuously over long-periods of time (e.g. 35 minutes in field-hockey or 45 minutes in soccer), current vision-based tracking approaches are not reliable enough to provide fully automatic solutions. As such, human intervention is required to fix-up missed or false detections. However, in instances where a human can not intervene due to the sheer amount of data being generated - this data can not be used due to the missing/noisy data. In this paper, we investigate two representations based on raw player detections (and not tracking) which are immune to missed and false detections. Specifically, we show that both team occupancy maps and centroids can be used to detect team activities, while the occupancy maps can be used to retrieve specific team activities. An evaluation on over 8 hours of field hockey data captured at a recent international tournament demonstrates the validity of the proposed approach.

Theoretical and experimental characterisation of energy in an electrostatic discharge

Electrostatic discharges have been identified as the most likely cause in a number of incidents of fire and explosion with unexplained ignitions. The lack of data and suitable models for this ignition mechanism creates a void in the analysis to quantify the importance of static electricity as a credible ignition mechanism. Quantifiable hazard analysis of the risk of ignition by static discharge cannot, therefore, be entirely carried out with our current understanding of this phenomenon. The study of electrostatics has been ongoing for a long time. However, it was not until the wide spread use of electronics that research was developed for the protection of electronics from electrostatic discharges. Current experimental models for electrostatic discharge developed for intrinsic safety with electronics are inadequate for ignition analysis and typically are not supported by theoretical analysis. A preliminary simulation and experiment with low voltage was designed to investigate the characteristics of energy dissipation and provided a basis for a high voltage investigation. It was seen that for a low voltage the discharge energy represents about 10% of the initial capacitive energy available and that the energy dissipation was within 10 ns of the initial discharge. The potential difference is greatest at the initial break down when the largest amount of the energy is dissipated. The discharge pathway is then established and minimal energy is dissipated as energy dissipation becomes greatly influenced by other components and stray resistance in the discharge circuit. From the initial low voltage simulation work, the importance of the energy dissipation and the characteristic of the discharge were determined. After the preliminary low voltage work was completed, a high voltage discharge experiment was designed and fabricated. Voltage and current measurement were recorded on the discharge circuit allowing the discharge characteristic to be recorded and energy dissipation in the discharge circuit calculated. Discharge energy calculations show consistency with the low voltage work relating to discharge energy with about 30-40% of the total initial capacitive energy being discharged in the resulting high voltage arc. After the system was characterised and operation validated, high voltage ignition energy measurements were conducted on a solution of n-Pentane evaporating in a 250 cm3 chamber. A series of ignition experiments were conducted to determine the minimum ignition energy of n-Pentane. The data from the ignition work was analysed with standard statistical regression methods for tests that return binary (yes/no) data and found to be in agreement with recent publications. The research demonstrates that energy dissipation is heavily dependent on the circuit configuration and most especially by the discharge circuit's capacitance and resistance. The analysis established a discharge profile for the discharges studied and validates the application of this methodology for further research into different materials and atmospheres; by systematically looking at discharge profiles of test materials with various parameters (e.g., capacitance, inductance, and resistance). Systematic experiments looking at the discharge characteristics of the spark will also help understand the way energy is dissipated in an electrostatic discharge enabling a better understanding of the ignition characteristics of materials in terms of energy and the dissipation of that energy in an electrostatic discharge.

Young women's recent experience of labour and birth care in Queensland

Background Young parenthood continues to be an issue of concern in terms of clinical and psychosocial outcomes for mothers and their babies, with higher rates of medical complications such as preterm labour and hypertensive disease and a higher risk of depression. The aim of this study was to investigate how young age impacts on women's experience of intrapartum care. Methods Secondary analysis of data collected in a population based survey of women who had recently given birth in Queensland, comparing clinical and interpersonal aspects of the intrapartum maternity care experience for 237 eligible women aged 15–20 years and 6534 aged more than 20 years. Descriptive and multivariate analyses were undertaken. Results In the univariate analysis a number of variables were significantly associated with clinical aspects of labour and birth and perceptions of care: young women were more likely to birth in a public facility, to travel for birth and to live in less economically advantaged areas, to have a normal vaginal birth and to have one carer through labour. They were also less likely to report being treated with respect and kindness and talked to in a way they could understand. In logistic regression models, after adjustment for parity, other socio-demographic factors and mode of birth, younger mothers were still more likely to birth in a public facility, to travel for birth, to be more critical about interpersonal and aspects of care and the hospital or birth centre environment. Conclusion This study shows how experience of care during labour and birth is different for young women. Young women reported poorer quality interpersonal care which may well reflect an inferior care experience and stereotyping by health professionals, indicating a need for more effective staff engagement with young women at this time.