Adrot, A., & Aguerre, M. (2023). The Impact of conflicts on Data Sharing for Disaster Risk Reduction. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 43–53). Omaha, USA: University of Nebraska at Omaha.
Abstract: Cross-border regions are particularly exposed to hazards and require cooperation for Disaster Risk Reduction (DRR). Accordingly, multiple countries have been investing in technology and jointly innovate to share and process data against disasters. However, these countries’ capacity to share data depends on the history and the context of the border itself. Going further, conflicts between countries – may they be past, present or future – can radically question and endanger collaborative efforts to share data for DRR. This collaborative research, involving a cohort of master students and an NGO, explores the influence of conflicts on data sharing and cooperation for DRR. Still in progress, this research examines how conflicts affect data sharing and how DRR actors manage them. It is based on exploratory archive analysis of three distinct cases of cross-border DRR collaboration within the EU borders, as well as experts and actors interviewing. Preliminary findings reveal that conflicts affect DRR at three levels: i) actors, ii) interactions with DRR actors, iii) relations between local DRR actors and institutions. The expected contribution of this research is theoretical, practical and pedagogical.
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Anouck Adrot, & Mercedes Aguerre. (2022). Data Ecosystems and Disaster Risk Reduction in Cross-border Regions: Visioning from 2020 Roya Valley Flood Disaster. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 878–886). Tarbes, France.
Abstract: Knowledge on the practical support from data ecosystems to disaster risk reduction remains partial. More specifically, we misunderstand the drivers and challenges inherent to emergency data ecosystems development in cross-border regions. We also miss cases of data ecosystem building in those regions. This research addresses these gaps by abiding by the principles and guidelines of visioning, a prospective and collaborative research design. Based on qualitative interviewing and archive analysis of the case 2020 Roya Valley floods, this work provides a prospect of a segment of data ecosystem that involves an organizational field aiming at Disaster Risk Reduction (DRR) at the French-Italian border. Still in progress, this work provides a comprehensive narration of a fictious data ecosystem. The narration hints at the major benefits and challenges inherent to this potential data ecosystem. This work enriches our understanding of data ecosystems’ features and benefits to cooperation between organizations involved in emergencies at borders (such as governments, civil protection agencies, volunteer-based organizations). In future development it will propose an agenda to support practitioners in the development good practices related to data ecosystems.
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Josep Cobarsí, & Laura Calvet. (2020). Community resilience instruments: Chances of improvement through customization and integration? 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. 381–388). Blacksburg, VA (USA): Virginia Tech.
Abstract: Resilience is understood as the ability of a system, community or society exposed to hazards to resist, absorb, accommodate, adapt to, transform and recover from the effects of a hazard in a timely and efficient manner. So far, dozens of measurement instruments have been developed to measure community resilience to disasters, considering each one different types of hazards (general, natural, climate, man-made, etc.) and communities (general, urban, rural, etc.). However, none of these instruments has been widely adopted yet. In this context, we discuss important gaps for resilience research and practice. Then, we propose a conceptual framework to review community resilience instruments, so to enhance their improvement through two facets (or dimensions) we propose of customization and integration. This framework is characterized by the following properties for community resilience instruments: encapsulation, intelligibility, geographical focus, hazard range focus, connectivity, adaptability to dynamic conditions, datification, and stakeholders' involvement. We look forward to apply this framework to review a purposive sample of community resilience instruments regarding natural disasters.
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Tayler Ruggero, & Brian Tomaszewski. (2018). Geographic Information Capacity (GIC) Across International Scales: Comparing Institutional Structures of Germany to the United States. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1153–1155). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Over the last three decades, the number and severity of natural disasters all across the world has been increasing exponentially (Basher, 2006). This paper intends to consider geographic information capacity (GIC) as it relates to government, government regulated organizations, and international organizations, including the United Nations, and their involvement in disaster risk reduction and management. Specifically, the paper aims to understand similarities and differences and the connection between two governmental disaster management organizations, FEMA in the United States and BBK and THW in Germany. We present a comparative analysis on the two countries in terms of their organizational structures, how their structures affect geographic information capacity and how geographic information capacity is related to disaster risk reduction and disaster response. Future work can make comparisons across more countries, including developing countries, to see what structural changes can be made in government entities to help increase GIC when disaster strikes.
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Zachary Sutherby, & Brian Tomaszewski. (2018). Conceptualizing the Role Geographic Information Capacity has on Quantifying Ecosystem Services under the Framework of Ecological Disaster Risk Reduction (EcoDRR). In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 326–333). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: The use of ecosystems for EcoDRR is a beneficial and a viable option for community stakeholders. For example, ecosystems can mitigate the effects of hazards experienced in anthropogenic communities. Ecosystem services are the underlying reason for this benefit. EcoDRR is the idea of sustainable management, conservation, and restoration of ecosystems to maximize ecosystem services and reduce disaster risks and impacts. The use of geospatial technologies to monitor large-scale ecosystems are often subject to Geographic Information Capacity (GIC), or the ability of ecosystem stakeholders to utilize all existing geographic information, resources, and capacities to monitor ecosystem services. Though these tools are useful, currently there is not a tool that specifically quantifies ecosystem services in the context of DRR. The main contribution of this paper is a conceptual framework intended to quantify ecosystem services in the context of EcoDRR.
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