A SOA-driven business intelligence architecture

A business intelligence architecture comprises of different unique components to collect, transform, analyze and present the structured and unstructured raw data in simple formats to assist decision makers in making timely decisions. The introduction of service-oriented architecture (SOA) enables reusable services which are accessible over a network on demand. However, there is still a lack of academic literatures on the business intelligence architecture with service-oriented concept. Based upon various references on BI architectures from major vendors, a novel BI architecture that is built on service-oriented concept is presented and described in this paper. The proposed service-oriented architecture enables enterprises to deploy a more agile, flexible, cheaper, reusable, reliable and responsive BI applications in supporting decision making process.

Making sense of business intelligence : proposing a socio-technical framework for improved decision making in not-for-profit organisations

The authors of this paper argue that human intuition alone cannot be relied upon for strategic decision making in today’s business environment and that quality data intelligence is an imperative. The proposed project described in this paper is research-in-progress, action design research (ADR), to implement an appropriate information systems (IS) enabling enhanced organisational decision making. ADR is a new research method that draws on action research and design research in an organisational setting. In phase 1 of the project, a sociotechnical ‘sense-making’ approach is used to gather and analyse information and decision needs in a not-for-profit (NFP) association, Connections ACT. In phase 2, requirements are designed and modelled to build a conceptual framework that guides NFPs in improving business performance and reporting capability. Phase 3 is the evaluative stage when the framework is reflected upon and refined, with intervention in the organisation’s processes as a promising outcome.

Linking BI competency and assimilation through absorptive capacity: a conceptual framework

Business intelligence (BI) can help support decision-making processes and so contribute to improved BI assimilation and organisational performance. However, a BI undertaking may be effective and profitable for some organisations but not others. How can these differing outcomes be explained for those firms that have adopted BI systems? Drawing on the literature pertaining to absorptive capacity theory, IT competency, and BI assimilation we develop a conceptual framework to investigate the relationships between BI competency, absorptive capacity, and BI assimilation. This research provides insights for BI stakeholders in understanding the mediating role of organisational absorptive capacity within a complex BI environment, enabling many organisations that have implemented BI to leverage the benefits from their costly investments. The conceptual framework provides a sound basis for further research to shed light on the effects of BI competency and organisational absorptive capacity on BI assimilation. Contributions to research and practice are discussed.

Fuzzy logic for decision support in chronic care

Computerized clinical guidelines can provide significant benefits in terms of health outcomes and costs, however, their effective computer implementation presents significant problems. Vagueness and ambiguity inherent in natural language (textual) clinical guidelines makes them problematic for formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. In care plan on-line (CPOL), an intranet-based chronic disease care planning system for general practitioners (GPs) in use in South Australia, we formally treat fuzziness in interpretation of quantitative data, formulation of recommendations and unequal importance of clinical indicators. We use expert judgment on cases, as well as direct estimates by experts, to optimize aggregation operators and treat heterogeneous combinations of conjunction and disjunction that are present in the natural language decision rules formulated by specialist teams.

Appropriate choice of aggregation operators in fuzzy decision support systems

Fuzzy logic provides a mathematical formalism for a unified treatment of vagueness and imprecision that are ever present in decision support and expert systems in many areas. The choice of aggregation operators is crucial to the behavior of the system that is intended to mimic human decision making. This paper discusses how aggregation operators can be selected and adjusted to fit empirical data—a series of test cases. Both parametric and nonparametric regression are considered and compared. A practical application of the proposed methods to electronic implementation of clinical guidelines is presented

Mixed-initiative decision support for care planning based on clinical practice guidelines

Care Plan On-Line (CPOL) is an intranet based system that supports a “Coordinated Care” model for chronic/complex disease management. CPOL combines provision of solicited and unsolicited advice features based on integration of the electronic medical record (EMR) with its decision support logic. The objective is to support General Practitioners (GPs) in formulating a 12-month care plan of services such that: (a) the plan is proactive and patient-centered; (b) the GP is kept in awareness of project- and diseasespecific clinical practice guidelines; and (c) the support integrates with GP workflow in a natural fashion. A key feature of our approach is to blur the distinction of EMR and decision support by presenting guidelines in layers with the top-most being a problem-oriented presentation of patient status, progressing on through to patient-independent supporting evidence. In conjunction with a degree of automated inclusion of care planning services, the system demonstrates mixed user and software initiative. We describe the CPOL deployment setting, the challenges of guideline-based clinical decision support, our approach to guideline delivery, and the CPOL architecture.

Filtering mobile spam by support vector machine

Currently mobile spam has been a major menace to the development of wireless networks. In this paper, the mobile spam problem and its countermeasures are analysed. In particular, we propose a Support Vector Machine to filter mobile spam. This mobile spam filtering system can be deployed in current wireless networks and achieve good performance in protecting end users and operators from mobile spam. Legislation issues and challenges to defend mobile spam are also discussed in the latter part of this paper.

Fuzzy logic in clinical practice decision support systems

Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how fuzzy logic can be applied and give a set of heuristics for the clinical guideline knowledge engineer for addressing uncertainty in practice guidelines. We describe the specific applicability of fuzzy logic to the decision support behavior of Care Plan On-Line, an intranet-based chronic care planning system for General Practitioners.

Building information modelling project decision support framework

Building Information Modelling (BIM) is an information technology [IT] enabled approach to managing design data in the AEC/FM (Architecture, Engineering and Construction/ Facilities Management) industry. BIM enables improved interdisciplinary collaboration across distributed teams, intelligent documentation and information retrieval, greater consistency in building data, better conflict detection and enhanced facilities management. Despite the apparent benefits the adoption of BIM in practice has been slow. Workshops with industry focus groups were conducted to identify the industry needs, concerns and expectations from participants who had implemented BIM or were BIM “ready”. Factors inhibiting BIM adoption include lack of training, low business incentives, perception of lack of rewards, technological concerns, industry fragmentation related to uneven ICT adoption practices, contractual matters and resistance to changing current work practice. Successful BIM usage depends on collective adoption of BIM across the different disciplines and support by the client. The relationship of current work practices to future BIM scenarios was identified as an important strategy as the participants believed that BIM cannot be efficiently used with traditional practices and methods. The key to successful implementation is to explore the extent to which current work practices must change. Currently there is a perception that all work practices and processes must adopt and change for effective usage of BIM. It is acknowledged that new roles and responsibilities are emerging and that different parties will lead BIM on different projects. A contingency based approach to the problem of implementation was taken which relies upon integration of BIM project champion, procurement strategy, team capability analysis, commercial software availability/applicability and phase decision making and event analysis. Organizations need to understand: (a) their own work processes and requirements; (b) the range of BIM applications available in the market and their capabilities (c) the potential benefits of different BIM applications and their roles in different phases of the project lifecycle, and (d) collective supply chain adoption capabilities. A framework is proposed to support organizations selection of BIM usage strategies that meet their project requirements. Case studies are being conducted to develop the framework. The results of the preliminary design management case study is presented for contractor led BIM specific to the design and construct procurement strategy.

Managing negotiation knowledge with the goal of developing negotiation decision support systems

While Information Technology has been used to support negotiation there is little research in the domain of knowledge management in legal negotiation. In this paper we discuss the nature of negotiation knowledge and how such knowledge can be utilized to construct negotiation decision support systems. We conduct an in-depth examination of the notion of a BATNA (Best Alternative to a Negotiated Agreement) and given a useful BATNA, how we can use issue and preference elicitation and compensation and trade-off strategies to provide negotiation decision support. We conclude by indicating how current negotiation support systems can be extended to support Online Dispute Resolution and haw we can extend the Family_Winner system in light of the need to more adequately manage negotiation knowledge.

Trade-off manipulations in the development of negotiation decision support systems

Our model of negotiation for constructing Negotiation Decision Support Systems is based upon Principled Negotiation and uses trade-off manipulations in order to provide decision support. A resulting system, Family_Winner, was constructed using several information systems techniques. Trade-off Maps (a variant of Constraint Diagrams) are used to represent trade-off opportunities, while an empirically derived formula calculates the amount of compensation given to the ratings of issues remaining in dispute. The Issue Decomposition Hierarchy embedded in the system allows for the incorporation of sub-issues. Family_Winner was originally built for use in Australian Family Law. We believe our model can be extended for use in various other domains.

Family_Winner has been evaluated in the areas of industrial relations, international disputation and company disputes. Results from our evaluation suggest the system works satisfactorily in these domains. We conclude this paper by describing future projects that will develop and extend Family_Winner's functions and applicability.

Virtual melawati : 3D GIS as a decision support tool for urban planning

Virtual Melawati is an environment for developing expertise in the application of 3D interactive visualization and GIS (Geographic Information System) to address problems of the built environment and to test the model as a decision support tool in the context of the local planning authorities in Malaysia. The visual approach enables the integration of highly complex spatial GIS information such as the evolution and transformation of the urban precinct as well as the impact of planned developments into the decision making process. The study will examine the techniques of data acquisition, data reconstruction from physical to digital, urban analysis and visualization in constructing an interactive 3D GIS model to support and assist the decision making process in urban design and planning. The outcomes of the study will deliver an experimental test bed for improving decision making processes in urban planning and design utilizing 3D modeling and GIS. The project will accelerate the uptake of digital and multimedia methods in local government, facilitate current planning and consultation processes between councils and stakeholders and improve the dissemination and management of spatial information about urban environments.

A brief review of recent research trends on applications of computational and statistical techniques in financial and business intelligence

Artificial neural networks and statistical techniques like decision trees, discriminant analysis, logistic regression and survival analysis play a crucial role in Business Intelligence. These predictive analytical tools exploit patterns found in historical data to make predictions about future events. In this paper we have shown some recent developments of a few of these techniques in financial and business intelligence applications like fraud detection, bankruptcy prediction and credit rating scoring.

Integrating knowledge systems in local coastal management; the case of an estuary entrance management support system (EEMSS) in Australia

The management of social, economic, and ecological assets in coastal zones is fundamental to the maintenance and sustainability of coastal resources. A significant issue in this discussion is the role of governance structures. In Australia the governance of the coastal zone includes a range of institutional authorities, processes, and procedures that set the context for decision making about coastal management. As well as the formal institutional arrangements there is also a maze of other interests such as development commissions, NGOs, Indigenous Native Title holders and other stakeholders including recreational interests. A major issue for governance arrangements is the considerable gap that often exists between how those interests interpret and develop their positions especially when the knowledge is derived from different systems – scientific, managerial, lay and indigenous. This paper will explore the development of an Estuary Entrance Management Support System (EEMSS) in south west Victoria Australia. The EEMSS is a decision support tool to assist estuary managers in determining whether to artificially open a river mouth. A significant part of the process adopted was community participation which involved a ‘steps’ approach to engage local community groups and landholders. It is the process of engaging different knowledge systems in a meaningful conversation that has led to a system that now gains support from all of the stakeholders in the management of different estuaries. The paper will discuss the processes that surround the EEMSS and outline some lessons that arise in context of the ‘project state’.