Information Sharing and Coordination in Collaborative Flood Warning and Response Systems

Vittorio Nespeca, Tina Comes, Leonardo Alfonso

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
215 Downloads (Pure)

Abstract

The introduction of new information and communication technologies enables communities to share information and self-organize in the response to disasters. Crowd-sourcing approaches enable professional authorities to capture information from the ground in real-time. However, there is a gap between the professional and community-driven response: locally emergent initiatives may lack the overview needed for efficient coordination, while decisions taken by professionals may not consider the actual situation on the ground.
We study this information sharing and coordination gap through the lens of urban flood early warning and response systems. Based on a literature review combining academic articles as well as guidelines and reports from practice, we derive design principles for these systems. Considering the case study of Accra, specific requirements are individuated. The design principles are then used to address the requirements, resulting in a set of functionalities for a collaborative flood warning and response system. These functionalities provide the basis for further development and evaluation.
Original languageEnglish
Title of host publicationProceedings of 27th international conference on information systems development (ISD2018)
PublisherAssociation for Information Systems
Number of pages14
ISBN (Print)978-91-7753-876-9
Publication statusPublished - 2018
Event27th international conference on information systems development - Lund, Sweden
Duration: 22 Aug 201824 Aug 2018

Conference

Conference27th international conference on information systems development
Abbreviated titleISD2018
Country/TerritorySweden
CityLund
Period22/08/1824/08/18

Keywords

  • Community Response
  • Community Resilience
  • Impact-Based Forecasting and Warning Systems

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