Influence of Context on Decision Making during Requirements Elicitation

Requirements engineers should strive to get a better insight into decision making processes. During elicitation of requirements, decision making influences how stakeholders communicate with engineers, thereby affecting the engineers' understanding of requirements for the future information system. Empirical studies issued from Artificial Intelligence offer an adequate groundwork to understand how decision making is influenced by some particular contextual factors. However, no research has gone into the validation of such empirical studies in the process of collecting needs of the future system's users. As an answer, the paper empirically studies factors, initially identified by AI literature, that influence decision making and communication during requirements elicitation. We argue that the context's structure of the decision should be considered as a cornerstone to adequately study how stakeholders decide to communicate or not a requirement. The paper proposes a context framework to categorize former factors into specific families, and support the engineers during the elicitation process.Comment: appears in Proceedings of the 4th International Workshop on Acquisition, Representation and Reasoning with Contextualized Knowledge (ARCOE), 2012, Montpellier, France, held at the European Conference on Artificial Intelligence (ECAI-12

A knowledge server including tools for professional know-how transfer

This paper presents a research in progress on the use of knowledge engineering and knowledge management techniques for the development of a strategic approach for the transfer of professional know-how. This transfer is based on the design of devices for sharing and learning clearly identified knowledge in the oil industry domains. This work is based on a pilot study which was carried out in the PED department (Petroleum Engineering & Development) and it deals with upstream activity of the oil group Sonatrach. After the different phases of knowledge mapping, critical knowledge assessment, and strategic alignment, the KM process focus on knowledge elicitation, sharing, transfer and learning, based on design and implementation of specific tools called Knowledge Server, including Knowledge Books and e-Learning.E-learning, Knowledge management, Knowledge transfer, Knowledge engineering, Knowledge servers, Computer assisted human learning, Case study

Incorporating stakeholders’ knowledge in group decision-making

International audienc

Dealing with abstraction: Case study generalisation as a method for eliciting design patterns

Developing a pattern language is a non-trivial problem. A critical requirement is a method to support pattern writers with abstraction, so as they can produce generalised patterns. In this paper, we address this issue by developing a structured process of generalisation. It is important that this process is initiated through engaging participants in identifying initial patterns, i.e. directly dealing with the 'cold-start' problem. We have found that short case study descriptions provide a productive 'way into' the process for participants. We reflect on a 1-year interdisciplinary pan-European research project involving the development of almost 30 cases and over 150 patterns. We provide example cases, detailing the process by which their associated patterns emerged. This was based on a foundation for generalisation from cases with common attributes. We discuss the merits of this approach and its implications for pattern development

Expert Elicitation for Reliable System Design

This paper reviews the role of expert judgement to support reliability assessments within the systems engineering design process. Generic design processes are described to give the context and a discussion is given about the nature of the reliability assessments required in the different systems engineering phases. It is argued that, as far as meeting reliability requirements is concerned, the whole design process is more akin to a statistical control process than to a straightforward statistical problem of assessing an unknown distribution. This leads to features of the expert judgement problem in the design context which are substantially different from those seen, for example, in risk assessment. In particular, the role of experts in problem structuring and in developing failure mitigation options is much more prominent, and there is a need to take into account the reliability potential for future mitigation measures downstream in the system life cycle. An overview is given of the stakeholders typically involved in large scale systems engineering design projects, and this is used to argue the need for methods that expose potential judgemental biases in order to generate analyses that can be said to provide rational consensus about uncertainties. Finally, a number of key points are developed with the aim of moving toward a framework that provides a holistic method for tracking reliability assessment through the design process.Comment: This paper commented in: [arXiv:0708.0285], [arXiv:0708.0287], [arXiv:0708.0288]. Rejoinder in [arXiv:0708.0293]. Published at http://dx.doi.org/10.1214/088342306000000510 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Benefits realisation for healthcare

Following the emergent importance of benefits realisation applied to healthcare infrastructure and service development programs, HaCIRIC has undertaken a research initiative targeting the development of a robust and comprehensive Benefits Realisation (BeReal©) process. The resulting model is focusing on how benefits should be elicited at the initial strategic stages, and how benefits should be deployed, managed and traced along the lifecycle of a programme so their realisation contributes to successful health outcomes. Subsequently BeReal© aspires to be an appropriate method to drive and control the programme plan; providing tools and techniques for defining specific benefits. It also allows the measurement and evaluation of the extent to which those benefits are delivered. We have set ourselves the objective of identifying current best practices and demonstrate how to improve benefits realisation in healthcare infrastructure provision. The HaCIRIC team in active collaboration with leading industry partners have undertaken various case and comparator studies not only to define a business critical process but to set out an ideology which places benefits realisation at the heart of securing wholly integrated (collective) change. We believe that to deliver consistent high quality infrastructure and services within an ever changing investment model requires a different level of thinking and understanding towards benefits realisation. The challenge of answering community needs through intelligent investment in infrastructure is complex and demands a deeper and inclusive awareness and appreciation of how to deliver benefits and effectively allocate resources. The BeReal© initiative seeks to contribute methodologically and intends to help spending money intelligently, working with programme and project related stakeholders, securing that the best possible benefits are obtained for the overall healthcare communities. This report highlights selected performed initiatives and summarises BeReal© process’s major characteristics, covering far more than the follow-up of a competitive tendering process and of the development of a traditional business case. BeReal© copes with a detailed definition of changing activities, breakdown of (needs into) benefits that drive the investment, supports decision-making, proposes the development of controlling initiatives and suggests major awareness to the implementation of corrective actions. We seek to continue innovating, stimulate learning, contributing to an increase of health and care performance that properly answers to community needs and intelligently invests public and private resources