Modelling complex resource requirements in Business Process Management Systems

Real-world business processes are resource-intensive. In work environments human resources usually multitask, both human and non-human resources are typically shared between tasks, and multiple resources are sometimes necessary to undertake a single task. However, current Business Process Management Systems focus on task-resource allocation in terms of individual human resources only and lack support for a full spectrum of resource classes (e.g., human or non-human, application or non-application, individual or teamwork, schedulable or unschedulable) that could contribute to tasks within a business process. In this paper we develop a conceptual data model of resources that takes into account the various resource classes and their interactions. The resulting conceptual resource model is validated using a real-life healthcare scenario.

Information and communication technologies : catalysts for sustainable development

The concept of sustainable urban development has been pushed to the forefront of policy-making and politics as the world wakes up to the impacts of climate change and the effects of modern urban lifestyles. Today, sustainable development has become a very prominent element in the day-to-day debate on urban policy and the expression of that policy in urban planning and development decisions. As a result of this, during the last few years, sustainable development automation applications such as sustainable urban development decision support systems have become popular tools as they offer new opportunities for local governments to realise their sustainable development agendas. This chapter explores a range of issues associated with the application of information and communication technologies and decision support systems in the process of underpinning sustainable urban development. The chapter considers how information and communication technologies can be applied to enhance urban planning, raise environmental awareness, share decisions and improve public participation. It introduces and explores three web-based geographical information systems projects as best practice. These systems are developed as support tools to include public opinion in the urban planning and development processes, and to provide planners with comprehensive tools for the analysis of sustainable urban development variants in order to prepare the best plans for constructing sustainable urban communities and futures.

Analysis of the effect of negation on information retrieval of medical data

Most information retrieval (IR) models treat the presence of a term within a document as an indication that the document is somehow "about" that term, they do not take into account when a term might be explicitly negated. Medical data, by its nature, contains a high frequency of negated terms - e.g. "review of systems showed no chest pain or shortness of breath". This papers presents a study of the effects of negation on information retrieval. We present a number of experiments to determine whether negation has a significant negative affect on IR performance and whether language models that take negation into account might improve performance. We use a collection of real medical records as our test corpus. Our findings are that negation has some affect on system performance, but this will likely be confined to domains such as medical data where negation is prevalent.

Informed learning: a pedagogical construct attending simultaneously to information use and learning.

The idea of informed learning, applicable in academic, workplace and community settings, has been derived largely from a program of phenomenographic research in the field of information literacy, which has illuminated the experience of using information to learn. Informed learning is about simultaneous attention to information use and learning, where both information and learning are considered to be relational; and is built upon a series of key concepts such as second–order perspective, simultaneity, awareness, and relationality. Informed learning also relies heavily on reflection as a strategy for bringing about learning. As a pedagogical construct, informed learning supports inclusive curriculum design and implementation. This paper reports aspects of the informed learning research agenda which are currently being pursued at the Queensland University of Technology (QUT). The first part elaborates the idea of informed learning, examines the key concepts underpinning this pedagogical construct, and explains its emergence from the research base of the QUT Information Studies research team. The second presents a case, which demonstrates the ongoing development of informed learning theory and practice, through the development of inclusive informed learning for a culturally diverse higher education context.

A framework for successful enterprise systems implementation : preliminary findings from a case study

While critical success factors (CSFs) of enterprise system (ES) implementation are mature concepts and have received considerable attention for over a decade, researchers have very often focused on only a specific aspect of the implementation process or a specific CSF. Resultantly, there is (1) little research documented that encompasses all significant CSF considerations and (2) little empirical research into the important factors of successful ES implementation. This paper is part of a larger research effort that aims to contribute to understanding the phenomenon of ES CSFs, and reports on preliminary findings from a case study conducted at a Queensland University of Technology (QUT) in Australia. This paper reports on an empirically derived CSFs framework using a directed content analysis of 79 studies; from top IS outlets, employing the characteristics of the analytic theory, and from six different projects implemented at QUT.

Understanding shared services : an exploration of the IS literature

In a competitive environment, companies continuously innovate to offer superior services at lower costs. ‘Shared Services’ have been extensively adopted in practice as a means for improving organizational performance. Shared Services are considered most appropriate for support functions and are widely adopted in human resource management, finance and accounting, and more recently employed as an information systems (IS) function. As computer-based corporate information systems have become de facto and the backbone of administrative systems, the technical impediments to sharing have come down dramatically. As this trend continues, CIOs and IT professionals need a deeper understanding of the Shared Services phenomenon. Yet, analysis of IS academic literature reveals that Shared Services, though mentioned in more than 100 articles, has received little in depth attention. This paper investigates the current status of Shared Services in IS literature. The authors present a detailed review of literature from main IS journals and conferences. The paper concludes with a tentative operational definition, a list of perceived main objectives of Shared Services, and an agenda for related future research.

A Two-stage information filtering based on rough decision rule and pattern mining

Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.

Assessment of the influence of cultural barriers to HDR supervision of non-English speaking background (NESD) students in engineering and information technology (IT) disciplines

The paper details the results of the first phase of an on-going research into the sociocultural factors that influence the supervision of higher degrees research (HDR) engineering students in the Faculty of Built Environment and Engineering (BEE) and Faculty of Science and Technology (FaST) at Queensland University of Technology. A quantitative analysis was performed on the results from an online survey that was administered to 179 engineering students. The study reveals that cultural barriers impact their progression and developing confidence in their research programs. We argue that in order to assist international and non-English speaking background (NESB) research students to triumph over such culturally embedded challenges in engineering research, it is important for supervisors to understand this cohort's unique pedagogical needs and develop intercultural sensitivity in their pedagogical practice in postgraduate research supervision. To facilitate this, the governing body (Office of Research) can play a vital role in not only creating the required support structures but also their uniform implementation across the board.

How do public librarians constitute information literacy?

To date, much work has been done to examine the ways in which information literacy – a way of thinking about, existing alongside and working with information- functions in an academic setting. However, its role in the non-academic library professions has been largely ignored. Given that the public librarian is responsible for designing and delivering services and programmes aimed at supporting the information literacy needs of the community-at-large there is great value to be had from examining the ways in which public libraries understand and experience IL. The research described in this paper investigates, through the use of phenomenography; the ways in which public librarians understand and experience the concept of Information Literacy.

Pattern-Based Evaluation of Scientific Workflow Management Systems

In recent years several scientific Workflow Management Systems (WfMSs) have been developed with the aim to automate large scale scientific experiments. As yet, many offerings have been developed, but none of them has been promoted as an accepted standard. In this paper we propose a pattern-based evaluation of three among the most widely used scientific WfMSs: Kepler, Taverna and Triana. The aim is to compare them with traditional business WfMSs, emphasizing the strengths and deficiencies of both systems. Moreover, a set of new patterns is defined from the analysis of the three considered systems.

Using Association Rules to Solve the Cold-Start Problem in Recommender Systems

Recommender systems are widely used online to help users find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus it is difficult for a recommender system to make quality recommendations. This problem is known as the cold-start problem. Here we investigate using association rules as a source of information to expand a user profile and thus avoid this problem. Our experiments show that it is possible to use association rules to noticeably improve the performance of a recommender system under the cold-start situation. Furthermore, we also show that the improvement in performance obtained can be achieved while using non-redundant rule sets. This shows that non-redundant rules do not cause a loss of information and are just as informative as a set of association rules that contain redundancy.

A review of rationale for allocating costs and payments in producing and supplying public sector information PART A of 2 Parts – Chapters 1, 2 and 3) 13 March 2011 version

This work reviews the rationale and processes for raising revenue and allocating funds to perform information intensive activities that are pertinent to the work of democratic government. ‘Government of the people, by the people, for the people’ expresses an idea that democratic government has no higher authority than the people who agree to be bound by its rules. Democracy depends on continually learning how to develop understandings and agreements that can sustain voting majorities on which democratic law making and collective action depends. The objective expressed in constitutional terms is to deliver ‘peace, order and good government’. Meeting this objective requires a collective intellectual authority that can understand what is possible; and a collective moral authority to understand what ought to happen in practice. Facts of life determine that a society needs to retain its collective competence despite a continual turnover of its membership as people die but life goes on. Retaining this ‘collective competence’ in matters of self-government depends on each new generation: • acquiring a collective knowledge of how to produce goods and services needed to sustain a society and its capacity for self-government; • Learning how to defend society diplomatically and militarily in relation to external forces to prevent overthrow of its self-governing capacity; and • Learning how to defend society against divisive internal forces to preserve the authority of representative legislatures, allow peaceful dispute resolution and maintain social cohesion.

A hybrid Chinese information retrieval model

A distinctive feature of Chinese test is that a Chinese document is a sequence of Chinese with no space or boundary between Chinese words. This feature makes Chinese information retrieval more difficult since a retrieved document which contains the query term as a sequence of Chinese characters may not be really relevant to the query since the query term (as a sequence Chinese characters) may not be a valid Chinese word in that documents. On the other hand, a document that is actually relevant may not be retrieved because it does not contain the query sequence but contains other relevant words. In this research, we propose a hybrid Chinese information retrieval model by incorporating word-based techniques with the traditional character-based techniques. The aim of this approach is to investigate the influence of Chinese segmentation on the performance of Chinese information retrieval. Two ranking methods are proposed to rank retrieved documents based on the relevancy to the query calculated by combining character-based ranking and word-based ranking. Our experimental results show that Chinese segmentation can improve the performance of Chinese information retrieval, but the improvement is not significant if it incorporates only Chinese segmentation with the traditional character-based approach.

Developing trust networks based on user tagging information for recommendation making

Recommender systems are one of the recent inventions to deal with ever growing information overload. Collaborative filtering seems to be the most popular technique in recommender systems. With sufficient background information of item ratings, its performance is promising enough. But research shows that it performs very poor in a cold start situation where previous rating data is sparse. As an alternative, trust can be used for neighbor formation to generate automated recommendation. User assigned explicit trust rating such as how much they trust each other is used for this purpose. However, reliable explicit trust data is not always available. In this paper we propose a new method of developing trust networks based on user’s interest similarity in the absence of explicit trust data. To identify the interest similarity, we have used user’s personalized tagging information. This trust network can be used to find the neighbors to make automated recommendations. Our experiment result shows that the proposed trust based method outperforms the traditional collaborative filtering approach which uses users rating data. Its performance improves even further when we utilize trust propagation techniques to broaden the range of neighborhood.