A Personalized Ontology Model for Web Information Gathering

As a model for knowledge description and formalization, ontologies are widely used to represent user profiles in personalized web information gathering. However, when representing user profiles, many models have utilized only knowledge from either a global knowledge base or a user local information. In this paper, a personalized ontology model is proposed for knowledge representation and reasoning over user profiles. This model learns ontological user profiles from both a world knowledge base and user local instance repositories. The ontology model is evaluated by comparing it against benchmark models in web information gathering. The results show that this ontology model is successful.

Performance analysis of business process models with advanced constructs

The importance of actively managing and analysing business processes is acknowledged more than ever in organisations nowadays. Business processes form an essential part of an organisation and their application areas are manifold. Most organisations keep records of various activities that have been carried out for auditing purposes, but they are rarely used for analysis purposes. This paper describes the design and implementation of a process analysis tool that replays, analyses and visualises a variety of performance metrics using a process definition and its corresponding execution logs. The replayer uses a YAWL process model example to demonstrate its capacity to support advanced language constructs.

A qualitative study of older adults’ responses to sitting-time questions : do we get the information we want?

Background: In the last decade, there has been increasing interest in the health effects of sedentary behavior, which is often assessed using self-report sitting-time questions. The aim of this qualitative study was to document older adults’ understanding of sitting-time questions from the International Physical Activity (PA) Questionnaire (IPAQ) and the PA Scale for the Elderly (PASE). Methods: Australian community-dwelling adults aged 65+ years answered the IPAQ and PASE sitting questions in face-to-face semi-structured interviews. IPAQ uses one open-ended question to assess sitting on a weekday in the last 7 days 'at work, at home, while doing coursework and during leisure time'; PASE uses a three-part closed question about daily leisure-time sitting in the last 7 days. Participants expressed their thoughts out loud while answering each question. They were then probed about their responses. Interviews were recorded, transcribed and coded into themes. Results: Mean age of the 28 male and 27 female participants was 73 years (range 65-89). The most frequently reported activity was watching TV. For both questionnaires, many participants had difficulties understanding what activities to report. Some had difficulty understanding what activities should be classified as ‘leisure-time sitting’. Some assumed they were being asked to only report activities provided as examples. Most reported activities they normally do, rather than those performed on a day in the previous week. Participants used a variety of strategies to select ‘a day’ for which they reported their sitting activities and to calculate sitting time on that day. Therefore, many different ways of estimating sitting time were used. Participants had particular difficulty reporting their daily sitting-time when their schedules were not consistent across days. Some participants declared the IPAQ sitting question too difficult to answer. Conclusion: The accuracy of older adults’ self-reported sitting time is questionable given the challenges they have in answering sitting-time questions. Their responses to sitting-time questions may be more accurate if our recommendations for clarifying the sitting domains, providing examples relevant to older adults and suggesting strategies for formulating responses are incorporated. Future quantitative studies should include objective criterion measures to assess validity and reliability of these questions.

Green IT : a matter of business and information systems engineering?

This panel discusses the impact of Green IT on information systems and how information systems can meet environmental challenges and ensure sustainability. We wish to highlight the role of green business processes, and specifically the contributions that the management of these processes can play in leveraging the transformative power of IS in order to create an environmentally sustainable society. The management of business processes has typically been thought of in terms of business improvement alongside the dimensions time, cost, quality, or flexibility – the so-called ‘devil’s quadrangle’. Contemporary organizations, however, increasingly become aware of the need to create more sustainable, IT-enabled business processes that are also successful in terms of their economic, ecological, as well as social impact. Exemplary ecological key performance indicators that increasingly find their way into the agenda of managers include carbon emissions, data center energy, or renewable energy consumption (SAP 2010). The key challenge, therefore, is to extend the devil’s quadrangle to a devil’s pentagon, including sustainability as an important fifth dimension in process change.

Semantic modeling method for configurable enterprise information systems

Business practices vary from one company to another and business practices often need to be changed due to changes of business environments. To satisfy different business practices, enterprise systems need to be customized. To keep up with ongoing business practice changes, enterprise systems need to be adapted. Because of rigidity and complexity, the customization and adaption of enterprise systems often takes excessive time with potential failures and budget shortfall. Moreover, enterprise systems often drag business behind because they cannot be rapidly adapted to support business practice changes. Extensive literature has addressed this issue by identifying success or failure factors, implementation approaches, and project management strategies. Those efforts were aimed at learning lessons from post implementation experiences to help future projects. This research looks into this issue from a different angle. It attempts to address this issue by delivering a systematic method for developing flexible enterprise systems which can be easily tailored for different business practices or rapidly adapted when business practices change. First, this research examines the role of system models in the context of enterprise system development; and the relationship of system models with software programs in the contexts of computer aided software engineering (CASE), model driven architecture (MDA) and workflow management system (WfMS). Then, by applying the analogical reasoning method, this research initiates a concept of model driven enterprise systems. The novelty of model driven enterprise systems is that it extracts system models from software programs and makes system models able to stay independent of software programs. In the paradigm of model driven enterprise systems, system models act as instructors to guide and control the behavior of software programs. Software programs function by interpreting instructions in system models. This mechanism exposes the opportunity to tailor such a system by changing system models. To make this true, system models should be represented in a language which can be easily understood by human beings and can also be effectively interpreted by computers. In this research, various semantic representations are investigated to support model driven enterprise systems. The significance of this research is 1) the transplantation of the successful structure for flexibility in modern machines and WfMS to enterprise systems; and 2) the advancement of MDA by extending the role of system models from guiding system development to controlling system behaviors. This research contributes to the area relevant to enterprise systems from three perspectives: 1) a new paradigm of enterprise systems, in which enterprise systems consist of two essential elements: system models and software programs. These two elements are loosely coupled and can exist independently; 2) semantic representations, which can effectively represent business entities, entity relationships, business logic and information processing logic in a semantic manner. Semantic representations are the key enabling techniques of model driven enterprise systems; and 3) a brand new role of system models; traditionally the role of system models is to guide developers to write system source code. This research promotes the role of system models to control the behaviors of enterprise.

What information counts at the moment of practice? Information practices of renal nurses

Aims. This article is a report of a study done to identify how renal nurses experience information about renal care and the information practices that they used to support everyday practice. Background. What counts as nursing knowledge remains a contested area in the discipline yet little research has been undertaken. Information practice encompasses a range of activities such as seeking, evaluation and sharing of information. The ability to make informed judgement is dependent on nurses being able to identify relevant sources of information that inform their practice and those sources of information may enable the identification of what knowledge is important to nursing practice. Method. The study was philosophically framed from a practice perspective and informed by Habermas and Schatzki; it employed qualitative research techniques. Using purposive sampling six registered nurses working in two regional renal units were interviewed during 2009 and data was thematically analysed. Findings. The information practices of renal nurses involved mapping an information landscape in which they drew on information obtained from epistemic, social and corporeal sources. They also used coupling, a process of drawing together information from a range of sources, to enable them to practice. Conclusion. Exploring how nurses engage with information, and the role the information plays in situating and enacting epistemic, social and corporeal knowledge into everyday nursing practice is instructive because it indicates that nurses must engage with all three modalities in order to perform effectively, efficiently and holistically in the context of patient care. © 2011 The Authors. Journal of Advanced Nursing © 2011 Blackwell Publishing Ltd.

Exploring the role of the governing body (board) in information technology governance : a study of Australian universities

In this thesis, I advance the understanding of information technology (IT) governance research and corporate governance research by considering the question “How do boards govern IT?” The importance of IT to business has increased over the last decade, but there has been little academic research which has focused on boards and their role in the governance of IT (Van Grembergen, De Haes and Guldentops, 2004). Most of the research on information technology governance (ITG) has focused on advancing the understanding and measurement of the components of the ITG model (Buckby, Best & Stewart, 2008; Wilkin & Chenhall, 2010), a model recommended by the IT Governance Institute (2003) as ‘best practice’ for boards to use in governing IT. IT governance is considered to be the responsibility of the board and is said to form an important subset of an organisation’s corporate governance processes (Borth & Bradley, 2008). Boards need to govern IT as a result of the large capital investment in IT resources and high dependency on IT by organisations. Van Grembergen, De Haes and Guldentops (2004) and De Haes & Van Grembergen (2009) indicate that corporate governance matters are not able to be effectively discharged unless IT is being governed properly, and call for further specific research on the role of the board in ITG. Researchers also indicate that the link between corporate governance and IT governance has been neglected (Borth & Bradley, 2008; Musson & Jordan, 2005; Bhattacharjya & Chang, 2008). This thesis will address this gap in the ITG literature by providing the bridge between the ITG and corporate governance literatures. My thesis uses a critical realist epistemology and a mixed method approach to gather insights into my research question. In the first phase of my research I develop a survey instrument to assess whether boards consider the components of the ITG model in governing IT. The results of this first study indicated that directors do not conceptualise their role in governing IT using the elements of the ITG model. Thus, I moved to focus on whether prominent corporate governance theories might elucidate how boards govern IT. In the second phase of the research, I used a qualitative inductive case based study to assess whether agency, stewardship and resource dependence theories explain how boards govern IT in Australian universities. As the first in-depth study of university IT governance processes, my research contributes to the ITG research field by revealing that Australian university board governance of IT is characterized by a combination of agency theory and stewardship theory behaviours and processes. The study also identified strong links between a university’s IT structure and evidence of agency and stewardship theories. This link provides insight into the structures element of the emerging enterprise governance of IT framework (Van Grembergen, De Haes & Guldentops, 2004; De Haes & Van Grembergen, 2009; Van Grembergen & De Haes, 2009b; Ko & Fink, 2010). My research makes an important contribution to governance research by identifying a key link between corporate and ITG literatures and providing insight into board IT governance processes. The research conducted in my thesis should encourage future researchers to continue to explore the links between corporate and IT governance research.

Information extraction from web services : a comparison of Tokenisation algorithms

Most web service discovery systems use keyword-based search algorithms and, although partially successful, sometimes fail to satisfy some users information needs. This has given rise to several semantics-based approaches that look to go beyond simple attribute matching and try to capture the semantics of services. However, the results reported in the literature vary and in many cases are worse than the results obtained by keyword-based systems. We believe the accuracy of the mechanisms used to extract tokens from the non-natural language sections of WSDL files directly affects the performance of these techniques, because some of them can be more sensitive to noise. In this paper three existing tokenization algorithms are evaluated and a new algorithm that outperforms all the algorithms found in the literature is introduced.

Car following model improvement for traffic safety metrics reproduction

Car Following models have a critical role in all microscopic traffic simulation models. Current microscopic simulation models are unable to mimic the unsafe behaviour of drivers as most are based on presumptions about the safe behaviour of drivers. Gipps model is a widely used car following model embedded in different micro-simulation models. This paper examines the Gipps car following model to investigate ways of improving the model for safety studies application. The paper puts forward some suggestions to modify the Gipps model to improve its capabilities to simulate unsafe vehicle movements (vehicles with safety indicators below critical thresholds). The result of the paper is one step forward to facilitate assessing and predicting safety at motorways using microscopic simulation. NGSIM as a rich source of vehicle trajectory data for a motorway is used to extract its relatively risky events. Short following headways and Time To Collision are used to assess critical safety event within traffic flow. The result shows that the modified proposed car following to a certain extent predicts the unsafe trajectories with smaller error values than the generic Gipps model.

Open problems in the security of learning

Machine learning has become a valuable tool for detecting and preventing malicious activity. However, as more applications employ machine learning techniques in adversarial decision-making situations, increasingly powerful attacks become possible against machine learning systems. In this paper, we present three broad research directions towards the end of developing truly secure learning. First, we suggest that finding bounds on adversarial influence is important to understand the limits of what an attacker can and cannot do to a learning system. Second, we investigate the value of adversarial capabilities-the success of an attack depends largely on what types of information and influence the attacker has. Finally, we propose directions in technologies for secure learning and suggest lines of investigation into secure techniques for learning in adversarial environments. We intend this paper to foster discussion about the security of machine learning, and we believe that the research directions we propose represent the most important directions to pursue in the quest for secure learning.