The future of enterprise groupware applications

This paper provides a review of groupware technology and products. The purpose of this review is to investigate the appropriateness of current groupware technology as the basis for future enterprise systems and evaluate its role in realising, the currently emerging, Virtual Enterprise model for business organisation. It also identifies in which way current technological phenomena will transform groupware technology and will drive the development of the enterprise systems of the future

Designing Software Architectures As a Composition of Specializations of Knowledge Domains

This paper summarizes our experimental research and software development activities in designing robust, adaptable and reusable software architectures. Several years ago, based on our previous experiences in object-oriented software development, we made the following assumption: ‘A software architecture should be a composition of specializations of knowledge domains’. To verify this assumption we carried out three pilot projects. In addition to the application of some popular domain analysis techniques such as use cases, we identified the invariant compositional structures of the software architectures and the related knowledge domains. Knowledge domains define the boundaries of the adaptability and reusability capabilities of software systems. Next, knowledge domains were mapped to object-oriented concepts. We experienced that some aspects of knowledge could not be directly modeled in terms of object-oriented concepts. In this paper we describe our approach, the pilot projects, the experienced problems and the adopted solutions for realizing the software architectures. We conclude the paper with the lessons that we learned from this experience

How are population-based funding formulae for healthcare composed?

Population-based funding formulae act as an important means of promoting equitable health funding structures. To evaluate how policy makers in different jurisdictions construct health funding formulae and build an understanding of contextual influences underpinning formula construction we carried out a comparative analysis of key components of funding formulae across seven high-income and predominantly publically financed health systems: New Zealand, England, Scotland, the Netherlands, the state of New South Wales in Australia, the Canadian province of Ontario, and the city of Stockholm, Sweden.Methods Core components from each formula were summarised and key similarities and differences evaluated from a compositional perspective. We categorised approaches to constructing funding formulae under three main themes: identifying factors which predict differential need amongst populations; adjusting for cost factors outside of needs factors; and engaging in normative correction of allocations for ‘unmet’ need. Results We found significant congruence in the factors used to guide need and cost adjustments. However, there is considerable variation in interpretation and implementation of these factors. Conclusion Despite broadly similar frameworks, there are distinct differences in the composition of the formulae across the seven health systems. Ultimately, the development of funding formulae is a dynamic process, subject to availability of data reflecting health needs, the influence of wider socio-political objectives and health system determinants

Compositional data for global monitoring: the case of drinking water and sanitation

Introduction At a global level, access to safe drinking water and sanitation has been monitored by the Joint Monitoring Programme (JMP) of WHO and UNICEF. The methods employed are based on analysis of data from household surveys and linear regression modelling of these results over time. However, there is evidence of non-linearity in the JMP data. In addition, the compositional nature of these data is not taken into consideration. This article seeks to address these two previous shortcomings in order to produce more accurate estimates. Methods We employed an isometric log-ratio transformation designed for compositional data. We applied linear and non-linear time regressions to both the original and the transformed data. Specifically, different modelling alternatives for non-linear trajectories were analysed, all of which are based on a generalized additive model (GAM). Results and discussion Non-linear methods, such as GAM, may be used for modelling non-linear trajectories in the JMP data. This projection method is particularly suited for data-rich countries. Moreover, the ilr transformation of compositional data is conceptually sound and fairly simple to implement. It helps improve the performance of both linear and non-linear regression models, specifically in the occurrence of extreme data points, i.e. when coverage rates are near either 0% or 100%.Peer ReviewedPostprint (author's final draft

Abstraction and Learning for Infinite-State Compositional Verification

Despite many advances that enable the application of model checking techniques to the verification of large systems, the state-explosion problem remains the main challenge for scalability. Compositional verification addresses this challenge by decomposing the verification of a large system into the verification of its components. Recent techniques use learning-based approaches to automate compositional verification based on the assume-guarantee style reasoning. However, these techniques are only applicable to finite-state systems. In this work, we propose a new framework that interleaves abstraction and learning to perform automated compositional verification of infinite-state systems. We also discuss the role of learning and abstraction in the related context of interface generation for infinite-state components.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455

A review of landscape rehabilitation frameworks in ecosystem engineering for mine closure

Mining causes changes to the environment and rehabilitation is necessary at mine closure. There is a lack of appropriate frameworks for mine site rehabilitation. In most cases, restoring the mine to previous conditions is challenging. Alternatively, mining companies can engineer ecosystems to suit new site conditions and aim for a self-sustaining and resilient ecosystem. In ecosystem design there should be consideration of the four key dimensions of any ecosystem; landscape, function, structure and composition (LFSC). Alcoa’s Bauxite mines and Barrick (Cowal) Limited’s Gold Mine have considered LFSC in their rehabilitation practices. From this, a framework based on LFSC is proposed as a means of planning, undertaking and monitoring mine rehabilitation, which together aim for a self-sustaining and resilient ecosystem. Elements of this framework are being utilised in the industry, and are supported by research. The framework could be used as an industry standard, utilised by regulatory bodies and potentially used in conjunction with other models and in other rehabilitation environments