On Merging Business Process Management and Geographic Information Systems : Modeling and Execution of Ecological Concerns in Processes

Business Process Management describes a holistic management approach for the systematic design, modeling, execution, validation, monitoring and improvement of organizational business processes. Traditionally, most attention within this community has been given to control-flow aspects, i.e., the ordering and sequencing of business activities, oftentimes in isolation with regards to the context in which these activities occur. In this paper, we propose an approach that allows executable process models to be integrated with Geographic Information Systems. This approach enables process models to take geospatial and other geographic aspects into account in an explicit manner both during the modeling phase and the execution phase. We contribute a structured modeling methodology, based on the well-known Business Process Model and Notation standard, which is formalized by means of a mapping to executable Colored Petri nets. We illustrate the feasibility of our approach by means of a sustainability-focused case example of a process with important ecological concerns.

A framework for qualitative analysis of focus group data in information systems

Focus groups are a popular qualitative research method for information systems researchers. However, compared with the abundance of research articles and handbooks on planning and conducting focus groups, surprisingly, there is little research on how to analyse focus group data. Moreover, those few articles that specifically address focus group analysis are all in fields other than information systems, and offer little specific guidance for information systems researchers. Further, even the studies that exist in other fields do not provide a systematic and integrated procedure to analyse both focus group ‘content’ and ‘interaction’ data. As the focus group is a valuable method to answer the research questions of many IS studies (in the business, government and society contexts), we believe that more attention should be paid to this method in the IS research. This paper offers a systematic and integrated procedure for qualitative focus group data analysis in information systems research.

Industry-government collaboration : Queensland's IT&T Strategy and the Information Industries Board

This paper presents a field study of the Queensland Information Technology and Telecommunications Industry Strategy (QITIS), and of the Information Industries Board (IIB), a joint industry-state government body established in 1992 to oversee the implementation of that strategy for the development of the IT&T Industry in Queensland. The aim of the study was to analyse differing stakeholder perspectives on the strategy and on its implementation by the IIB. The study forms part of a longer-term review which aims to develop methodologies for the selection of appropriate strategies for the IT&T Industry, and for the evaluation of outcomes of strategy.

Bayesian networks for information synthesis in complex systems

This thesis introduces a method of applying Bayesian Networks to combine information from a range of data sources for effective decision support systems. It develops a set of techniques in development, validation, visualisation, and application of Complex Systems models, with a working demonstration in an Australian airport environment. The methods presented here have provided a modelling approach that produces highly flexible, informative and applicable interpretations of a system's behaviour under uncertain conditions. These end-to-end techniques are applied to the development of model based dashboards to support operators and decision makers in the multi-stakeholder airport environment. They provide highly flexible and informative interpretations and confidence in these interpretations of a system's behaviour under uncertain conditions.

Marginal costs of hospital-acquired conditions : information for priority-setting for patient safety programmes and research

Objective: To estimate the relative inpatient costs of hospital-acquired conditions. Methods: Patient level costs were estimated using computerized costing systems that log individual utilization of inpatient services and apply sophisticated cost estimates from the hospital's general ledger. Occurrence of hospital-acquired conditions was identified using an Australian ‘condition-onset' flag for diagnoses not present on admission. These were grouped to yield a comprehensive set of 144 categories of hospital-acquired conditions to summarize data coded with ICD-10. Standard linear regression techniques were used to identify the independent contribution of hospital-acquired conditions to costs, taking into account the case-mix of a sample of acute inpatients (n = 1,699,997) treated in Australian public hospitals in Victoria (2005/06) and Queensland (2006/07). Results: The most costly types of complications were post-procedure endocrine/metabolic disorders, adding AU$21,827 to the cost of an episode, followed by MRSA (AU$19,881) and enterocolitis due to Clostridium difficile (AU$19,743). Aggregate costs to the system, however, were highest for septicaemia (AU$41.4 million), complications of cardiac and vascular implants other than septicaemia (AU$28.7 million), acute lower respiratory infections, including influenza and pneumonia (AU$27.8 million) and UTI (AU$24.7 million). Hospital-acquired complications are estimated to add 17.3% to treatment costs in this sample. Conclusions: Patient safety efforts frequently focus on dramatic but rare complications with very serious patient harm. Previous studies of the costs of adverse events have provided information on ‘indicators’ of safety problems rather than the full range of hospital-acquired conditions. Adding a cost dimension to priority-setting could result in changes to the focus of patient safety programmes and research. Financial information should be combined with information on patient outcomes to allow for cost-utility evaluation of future interventions.

Social interaction and the role of empathy in information and knowledge management

This article provides a general review of the literature on the nature and role of empathy in social interaction for information professionals working in a variety of information and knowledge environments. Relational agency theory (Edwards, 2005) is used asa framework to re-conceptualize education for empathic social interaction between information professionals and their clients. Past, present and future issues relevant to empathic interaction in information and knowledge management are discussed in the context of three shifts identified from the literature: (a) the continued increase in communication channels, both physical and virtual, for reference, information and re-search services, (b) the transition from the information age to the conceptual age and(c) the growing need for understanding of the affective paradigm in the information and knowledge professions. Findings from the literature review on the relationships between empathy and information behavior, social networking, knowledge management and information and knowledge services are presented. Findings are discussed in relation to the development of guidelines for the affective education and training of information and knowledge professionals and the potential use of virtual learning software such as Second Life in developing empathic communication skills

A model for assessing information systems success and its application to e-logistics tracking systems

The DeLone and McLean (D&M) model (2003) has been broadly used and generally recognised as a useful model for gauging the success of IS implementations. However, it is not without limitations. In this study, we evaluate a model that extends the D&M model and attempts to address some of it slimitations by providing a more complete measurement model of systems success. To that end, we augment the D&M (2003) model and include three variables: business value, institutional trust, and future readiness. We propose that the addition of these variables allows systems success to be assessed at both the systems level and the business level. Consequently, we develop a measurement model rather than a structural or predictive model of systems success.

Citizens and social media in times of natural disaster: Exploring information experience

Introduction. Social media is becoming a vital source of information in disaster or emergency situations. While a growing number of studies have explored the use of social media in natural disasters by emergency staff, military personnel, medial and other professionals, very few studies have investigated the use of social media by members of the public. The purpose of this paper is to explore citizens’ information experiences in social media during times of natural disaster. Method. A qualitative research approach was applied. Data was collected via in-depth interviews. Twenty-five people who used social media during a natural disaster in Australia participated in the study. Analysis. Audio recordings of interviews and interview transcripts provided the empirical material for data analysis. Data was analysed using structural and focussed coding methods. Results. Eight key themes depicting various aspects of participants’ information experience during a natural disaster were uncovered by the study: connected; wellbeing; coping; help; brokerage; journalism; supplementary and characteristics. Conclusion. This study contributes insights into social media’s potential for developing community disaster resilience and promotes discussion about the value of civic participation in social media when such circumstances occur. These findings also contribute to our understanding of information experiences as a new informational research object.

Diagnose this if you can: On the effectiveness of search engines in finding medical self-diagnosis information

An increasing amount of people seek health advice on the web using search engines; this poses challenging problems for current search technologies. In this paper we report an initial study of the effectiveness of current search engines in retrieving relevant information for diagnostic medical circumlocutory queries, i.e., queries that are issued by people seeking information about their health condition using a description of the symptoms they observes (e.g. hives all over body) rather than the medical term (e.g. urticaria). This type of queries frequently happens when people are unfamiliar with a domain or language and they are common among health information seekers attempting to self-diagnose or self-treat themselves. Our analysis reveals that current search engines are not equipped to effectively satisfy such information needs; this can have potential harmful outcomes on people’s health. Our results advocate for more research in developing information retrieval methods to support such complex information needs.

A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

Computational analysis of epigenetic information in human DNA sequences

Over the last few years, investigations of human epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies across defined regions within the human genome, and to identify new patterns between epigenetic mechanisms and DNA content. Signal processing methods, including Fourier and Wavelet Transformations, are employed and principal results are reported.

Impact of mobility and topology on information diffusion in MANETs

In some delay-tolerant communication systems such as vehicular ad-hoc networks, information flow can be represented as an infectious process, where each entity having already received the information will try to share it with its neighbours. The random walk and random waypoint models are popular analysis tools for these epidemic broadcasts, and represent two types of random mobility. In this paper, we introduce a simulation framework investigating the impact of a gradual increase of bias in path selection (i.e. reduction of randomness), when moving from the former to the latter. Randomness in path selection can significantly alter the system performances, in both regular and irregular network structures. The implications of these results for real systems are discussed in details.

'I wonder what you know...': Teachers designing requests for factual information

The early years are significant in optimising children’s educational, emotional and social outcomes and have become a major international policy priority. Within Australia, policy levers have prioritised early childhood education, with a focus on program quality, as it is associated with lifelong success. Longitudinal studies have found that high quality teacher-child interactions are an essential element of high quality programs, and teacher questioning is one aspect of teacher-child interactions that has been attributed to affecting the quality of education, linking open ended questioning to higher cognitive achievement. Teachers, however, overwhelmingly ask more closed than open questions. In the classroom, like everyday interaction, questions in interaction require answers. They are used to request, offer, repair, challenge, seek agreement (Curl & Drew, 2008; Enfield, Stivers, & Levinson, 2010; Hayano, 2013; Schegloff, 2007). Teachers use questions to set agendas and manage lessons (McHoul, 1978; Mehan, 1979; Sacks, 1995), and to gauge students’ knowledge and understanding (Lerner, 1995; McHoul, 1978; Mehan, 1979). Drawing on data from the Australian Research Council project Interacting with Knowledge: Interacting with people: Web searching in early childhood, this paper focuses on an extended sequence of talk between a teacher with two students aged between 3.5 and 5 years in a preschool classroom. The episode, drawn from a corpus of over 200 hours of video recorded data, captures how the teacher and children undertake an online search for images of lady beetles and hairy caterpillars on the Web. Ethnomethodological and conversation analysis approaches examine how the teacher asks questions, which call on the children to display their factual knowledge about the search topic. The fine grained analysis shows how teachers design their interactions to prompt children’s displays of factual knowledge, and how the design of factual questions affect a student’s response in terms of what and how they respond. In focussing on how the teacher designs factual questions and how children respond to these questions it shows that question design can close down a student’s reply; or elicit a range of answers, from one word to extended more detailed responses. Understanding how the design of teachers’ questions can influence students’ responses has pedagogic implications and may support educators to make intentional decisions regarding their own questioning techniques.

Experiencing information use for early career academics’ learning: A knowledge ecosystem model

Purpose This study explores the informed learning experiences of early career academics while building their networks for professional and personal development. The notion that information and learning are inextricably linked via the concept of ‘informed learning’ is used as a conceptual framework to gain a clearer picture of what informs early career academics while they learn and how they experience using that which informs their learning within this complex practice: to build, maintain and utilise their developmental networks. Methodology This research employs a qualitative framework using a constructivist grounded theory approach (Charmaz, 2006). Through semi-structured interviews with a sample of fourteen early career academics from across two Australian universities, data were generated to investigate the research questions. The study used the methods of constant comparison to create codes and categories towards theme development. Further examination considered the relationship between thematic categories to construct an original theoretical model. Findings The model presented is a ‘knowledge ecosystem’, which represents the core informed learning experience. The model consists of informal learning interactions such as relating to information to create knowledge and engaging in mutually supportive relationships with a variety of knowledge resources found in people who assist in early career development. Originality/Value Findings from this study present an alternative interpretation of informed learning that is focused on processes manifesting as human interactions with informing entities revolving around the contexts of reciprocal human relationships.

Retrieving trip information from a discrete detectors network : The case of Brisbane Bluetooth detectors

Automatic Vehicle Identification Systems are being increasingly used as a new source of travel information. As in the last decades these systems relied on expensive new technologies, few of them were scattered along a networks making thus Travel-Time and Average Speed estimation their main objectives. However, as their price dropped, the opportunity of building dense AVI networks arose, as in Brisbane where more than 250 Bluetooth detectors are now installed. As a consequence this technology represents an effective means to acquire accurate time dependant Origin Destination information. In order to obtain reliable estimations, however, a number of issues need to be addressed. Some of these problems stem from the structure of a network made out of isolated detectors itself while others are inherent of Bluetooth technology (overlapping detection area, missing detections,\...). The aim of this paper is threefold: First, after having presented the level of details that can be reached with a network of isolated detectors we present how we modelled Brisbane's network, keeping only the information valuable for the retrieval of trip information. Second, we give an overview of the issues inherent to the Bluetooth technology and we propose a method for retrieving the itineraries of the individual Bluetooth vehicles. Last, through a comparison with Brisbane Transport Strategic Model results, we highlight the opportunities and the limits of Bluetooth detectors networks. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.