3 resultados para Accident Data

em CentAUR: Central Archive University of Reading - UK


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Widespread commercial use of the internet has significantly increased the volume and scope of data being collected by organisations. ‘Big data’ has emerged as a term to encapsulate both the technical and commercial aspects of this growing data collection activity. To date, much of the discussion of big data has centred upon its transformational potential for innovation and efficiency, yet there has been less reflection on its wider implications beyond commercial value creation. This paper builds upon normal accident theory (NAT) to analyse the broader ethical implications of big data. It argues that the strategies behind big data require organisational systems that leave them vulnerable to normal accidents, that is to say some form of accident or disaster that is both unanticipated and inevitable. Whilst NAT has previously focused on the consequences of physical accidents, this paper suggests a new form of system accident that we label data accidents. These have distinct, less tangible and more complex characteristics and raise significant questions over the role of individual privacy in a ‘data society’. The paper concludes by considering the ways in which the risks of such data accidents might be managed or mitigated.

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COCO-2 is a model for assessing the potential economic costs likely to arise off-site following an accident at a nuclear reactor. COCO-2 builds on work presented in the model COCO-1 developed in 1991 by considering economic effects in more detail, and by including more sources of loss. Of particular note are: the consideration of the directly affected local economy, indirect losses that stem from the directly affected businesses, losses due to changes in tourism consumption, integration with the large body of work on recovery after an accident and a more systematic approach to health costs. The work, where possible, is based on official data sources for reasons of traceability, maintenance and ease of future development. This report describes the methodology and discusses the results of an example calculation. Guidance on how the base economic data can be updated in the future is also provided.

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Data from four experimental research projects are presented which have in common that unexpected results caused a change in direction of the research. A plant growth accelerator caused the appearance of white black bean aphids, a synthetic pyrethroid suspected of enhancing aphid reproduction proved to enhance plant growth, a chance conversation with a colleague initiated a search for fungal DNA in aphids, and the accidental invasion of aphid cultures by a parasitoid reversed the aphid population ranking of two Brussels sprout cultivars. This last result led to a whole series of studies on the plant odour preferences of emerging parasitoids which in turn revealed the unexpected phenomenon that chemical cues to the maternal host plant are left with the eggs at oviposition. It is pointed out that, too often, researchers fail to follow up unexpected results because they resist accepting flaws in their hypotheses; also that current application criteria for research funding make it hard to accommodate unexpected findings.