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Fiona Jennet McNeill, Diana Bental, Jeremy Bryan, Paolo Missier, Jannetta S. Steyn, & Tom Kumar. (2019). Communication in Emergency Management through Data Integration and Trust: an introduction to the CEM-DIT system. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: This paper discusses the development of the CEM-DIT (Communication in Emergency Management through Data
Integration and Trust) system, which allows decision makers in crises to send out automated data requests to multiple
heterogeneous and potentially unknown sources and interactively determine how reliable, relevant and trustworthy
the responses are. We describe the underlying technology, which is based partially on data integration and matching,
and partly on utilisation of provenance data. We describe our cooperation with the Urban Observatory (UO), which
allows us to develop the system in collaboration with developers of the kind of crisis-relevant data which the system
is designed for. The system is currently in development, and we describe which parts are fully implemented and
which are currently being developed.
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Fiona Jennet McNeill, Diana Bental, Jeremy Bryans, Paolo Missier, & Jannetta Steyn. (2018). Informing decision makers: facilitating communication and trust for decision makers during crises. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1133–1135). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: This paper describes our approach to facilitating automated data sharing during a crisis management scenario. There are a number of reasons why this is difficult, of which we are addressing two of the main ones. Firstly, data in different organisations (and organisations) is mismatched in that different terminology, structure, specificity and data formats are used, so automated comprehension of data is problematic. Secondly, is that it is hard to assess the trustworthiness of data from other organisations. We have developed data-matching and provenance-based solutions to these problems individually. In this paper, we discuss how best these approaches can be integrated so that decision makers can quickly and automatically be presented with data to match, or approximately match, their data needs, together with the right information for them to understand the quality and meaning of this data, and introduce the CEM-DIT (Communication for Emergency Management through Data Integration and Trust) system.
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