Stella van Esch, Marc van den Homberg, & Kees Boersma. (2021). Looking Beyond the Data: an Assessment of the Emerging Data Ecosystem of Nepal's Flood Early Warning Systems. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 282–293). Blacksburg, VA (USA): Virginia Tech.
Abstract: Increasingly, data-driven instruments are used in disaster risk reduction to foster more efficient, effective, and evidence-based decision-making. This data revolution brings along opportunities and challenges, which are sometimes related to the data itself, but more often seem related to the environment in which the data is put to use. To provide insight into such an emerging data ecosystem, this paper uses a qualitative case study to assess the use of data in flood early warning systems (EWS) in Nepal. In response to the research question 'How does the data ecosystem impact the opportunities and challenges regarding data use in flood early warning systems in Nepal?', this paper discusses the importance of considering the broader context instead of regarding data as an entity unto itself. It shows how actors, policies and other contextual factors impact the effectiveness of data use by either presenting opportunities, like the establishment of a national disaster data repository, or challenges, like inadequate human resources for working with data.
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Teun Terpstra, & Hanneke Vreugdenhil. (2011). Filling in the blanks: Constructing effective flood warning messages using the Flood Warning Communicator (FWC). In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper reports the progress that is being made in developing a software tool (the Flood Warning Communicator, FWC) that helps communication professionals constructing effective flood-warning messages. The program provides authorities with a warning message that contains open spaces where event specific information can be inserted. The program uses a database containing (parts of) phrases. Based on the specific situation, a communication professional receives the most suitable standard phrase by clicking on information buttons in a user interface. Together, the phrases form the warning message that sometimes requires minor adjustments such that it suits the specific circumstances. FWC is a well working prototype that allows constructing messages for web sites and short text messages (sms). Research is needed to test and validate these warning messages. In addition, cooperation with public authorities is necessary to make the program suitable for local circumstances (e.g., safety regions and municipalities).
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Valerio Lorini, Javier Rando, Diego Saez-Trumper, & Carlos Castillo. (2020). Uneven Coverage of Natural Disasters in Wikipedia: The Case of Floods. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 688–703). Blacksburg, VA (USA): Virginia Tech.
Abstract: The usage of non-authoritative data for disaster management provides timely information that might not be available through other means. Wikipedia, a collaboratively-produced encyclopedia, includes in-depth information about many natural disasters, and its editors are particularly good at adding information in real-time as a crisis unfolds. In this study, we focus on the most comprehensive version of Wikipedia, the English one. Wikipedia offers good coverage of disasters, particularly those having a large number of fatalities. However, by performing automatic content analysis at a global scale, we also show how the coverage of floods in Wikipedia is skewed towards rich, English-speaking countries, in particular the US and Canada. We also note how coverage of floods in countries with the lowest income is substantially lower than the coverage of floods in middle-income countries. These results have implications for analysts and systems using Wikipedia as an information source about disasters.
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T.L. Van Zyl, C. Parbhoo, Moodley, Cwela, D. Umuhoza, P. Shabangu, et al. (2009). IT infrastructure enabling open access for flood risk preparedness in South Africa. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The paper focuses on the information technology infrastructure required for the evaluation and monitoring of risk relating to floods in South Africa. It may be argued that in the context of developing countries, flood preparedness is more valuable than the actual response to a flood disaster. The paper looks at this flood preparedness in the context of informal and semi-formal settlements. An information technology infrastructure is proposed that will allow decision makers to be alerted to possible flood high risk areas, and in so doing maximise preparedness.
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Anuradha Venkateswaran, Katrina Simon-Agolory, & Kera Z. Watkins. (2011). Risk analysis for Greene County and Wright Patterson Air Force Base, Ohio: Simulation of riverine flooding using HAZUS-MH. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Greene County in Dayton, OH houses Wright Patterson Air Force Base (WPAFB), whose estimated 2009 economic impact within its Metropolitan Statistical Area (MSA) is $5.17 million. Despite its military/strategic importance as the largest base in the U.S. Air Force, literature search did not uncover a published comprehensive risk analysis for WPAFB, or even Greene County, across the entire spectrum of hazards from natural to technological to man-made (including terrorism). This paper presents a summary report on risk determination and economic impact data for Greene County and WPAFB (within Greene County) in the context of riverine flooding, using FEMA's HAZUS-MH tool. It is hoped that the results will further the regional compilation of data and thus prove of use to the local disaster management community while generally growing the overall body of work in risk analysis. Future work aims to expand regional risk determination to other natural disasters and terrorism scenarios.
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Rene Windhouwer, Gerdien A. Klunder, & F.M. Sanders. (2005). Decision support system emergency planning, creating evacuation strategies in the event of flooding. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 171–180). Brussels: Royal Flemish Academy of Belgium.
Abstract: The Decision Support System (DSS) Emergency Planning is designed for use in the event of sea or river flooding. It makes accessible all the information related to the decision whether to evacuate an area. An important factor in this decision is the time required for the evacuation. The model used by the DSS Emergency Planning system to estimate the time required employs a strategy that prevents congestion on the road network in the area at risk. The use of the DSS Emergency Planning system during the proactive and prevention phases enables disaster containment organisations to prepare better for a flood situation. Moreover, all relevant information is saved and is therefore available for the post-disaster evaluation. The DSS Emergency Planning system can play a significant role in ensuring that the evacuation of an area at risk goes according to plan. In the future the DSS Emergency Planning system can also be used to evacuate people in the event of a nuclear, natural fire or extreme weather disaster.
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