Anouck Adrot, Samuel Auclair, Julien Coche, Audrey Fertier, Cécile Gracianne, & Aurélie Montarnal. (2022). Using Social Media Data in Emergency Management: A Proposal for a Socio-technical Framework and a Systematic Literature Review. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 470–479). Tarbes, France.
Abstract: Data represents an essential resource to the management of emergencies: organizations have been growingly investing in technologies and resources to lever data as an asset before, during, and after disasters and emergencies. However, research on data usage in emergency management remains fragmented, preventing practitioners and scholars from approaching data comprehensively. To address this gap, this research in progress consists of a systematic review of the literature in a two-steps approach: we first propose a socio-technical framework and use it in an exploratory mapping of the main topics covered by the literature. Our preliminary findings suggest that research on data usage primarily focuses on technological opportunities and affordances and, hence, lacks practical implementation aspects in organizations. The expected contribution is double. First, we contribute to a more comprehensive understanding of data usage in emergency management. Second, we propose future avenues for research on data and resilience.
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Audrey Fertier, Aurélie Montarnal, Anne-Marie Barthe-Delanoë, Sébastien Truptil, & Frédérick Bénaben. (2016). Adoption of Big Data in Crisis Management. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Most agree that the innate complexity and uncertainty of a crisis compel the stakeholders to coordinate in a hurry, despite their heterogeneity or the volume of data to process. Supporting their coordination is now possible, thanks to a mediation system combined with big data management tools. The GéNéPi1 project explores this possibility and proposes to improve the generation of collaborative processes offered by the MISE2?s solution. The idea is to increase the number of usable data sources. To do that, in a fixed time-frame, the situation models have to be instantly generated upon sets of raw data. This new methodology holds the key to a new big data era: an age where global understanding reigns.
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Audrey Fertier, Aurélie Montarnal, Sébastien Truptil, Anne-Marie Barthe-Delanoë, & Frédérick Bénaben. (2017). A situation model to support collaboration and decision-making inside crisis cells, in real time. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 1020–1028). Albi, France: Iscram.
Abstract: Natural and man-made hazards have many unexpected consequences that concern as many heterogeneous services. The GéNéPi project offers to support officials in addressing those events: its purpose is to support the collaboration in the field and the decision-making in the crisis cells. To succeed, the GéNéPi system needs to be aware of the ongoing crisis developments. For now, its best chance is to benefit from the ever growing number of available data sources. One of its goals is, therefore, to learn how to manage numerous, heterogeneous, more or less reliable data, in order to interpret them, in time, for the officials. The result consists on a situation model in the shape of a common operational picture. This paper describes every stage of modelling from the raw data selection, to the use of the situation model itself.
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