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Crowdsourcing roles, methods and tools for data-intensive disaster management

Author

Listed:
  • Marta Poblet

    (RMIT University)

  • Esteban García-Cuesta

    (Universidad Europea de Madrid)

  • Pompeu Casanovas

    (UAB Institute of Law and Technology
    Deakin University)

Abstract

Mobile technologies, web-based platforms, and social media have transformed the landscape of disaster management by enabling a new generation of digital networks to produce, process, and analyse georeferenced data in real time. This unprecedented convergence of geomobile technologies and crowdsourcing methods is opening up multiple forms to participate in disaster management tasks. Based on empirical research, this paper first proposes a conceptualisation of crowdsourcing roles and then analyses methods and tools based on a combination of two variables: (i) types of data being processed; (ii) involvement of the crowds. The paper also surveys a number of existing platforms and mobile apps leveraging crowdsourcing in disaster and emergency management with the aim to contribute to the discussion on the advantages and limits of using crowdsourcing methods and tools in these areas.

Suggested Citation

  • Marta Poblet & Esteban García-Cuesta & Pompeu Casanovas, 2018. "Crowdsourcing roles, methods and tools for data-intensive disaster management," Information Systems Frontiers, Springer, vol. 20(6), pages 1363-1379, December.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:6:d:10.1007_s10796-017-9734-6
    DOI: 10.1007/s10796-017-9734-6
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    References listed on IDEAS

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    4. Yuxiang Zhao & Qinghua Zhu, 2014. "Evaluation on crowdsourcing research: Current status and future direction," Information Systems Frontiers, Springer, vol. 16(3), pages 417-434, July.
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    Cited by:

    1. Hamid Bahadori & Hamed Vahdat-Nejad & Hossein Moradi, 2022. "CrowdBIG: crowd-based system for information gathering from the earthquake environment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3719-3741, December.
    2. Ling Tan & Ji Guo & Selvarajah Mohanarajah & Kun Zhou, 2021. "Can we detect trends in natural disaster management with artificial intelligence? A review of modeling practices," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2389-2417, July.
    3. Sahil & Sandeep Kumar Sood, 2021. "Bibliometric monitoring of research performance in ICT-based disaster management literature," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(1), pages 103-132, February.
    4. Gupta, Shivam & Modgil, Sachin & Kumar, Ajay & Sivarajah, Uthayasankar & Irani, Zahir, 2022. "Artificial intelligence and cloud-based Collaborative Platforms for Managing Disaster, extreme weather and emergency operations," International Journal of Production Economics, Elsevier, vol. 254(C).
    5. Yanxin Wang & Jian Li & Xi Zhao & Gengzhong Feng & Xin (Robert) Luo, 2020. "Using Mobile Phone Data for Emergency Management: a Systematic Literature Review," Information Systems Frontiers, Springer, vol. 22(6), pages 1539-1559, December.
    6. Tenanoia Simona & Tauisi Taupo & Pedro Antunes, 2023. "A Scoping Review on Agency Collaboration in Emergency Management Based on the 3C Model," Information Systems Frontiers, Springer, vol. 25(1), pages 291-302, February.
    7. Josip Marić & Carlos Galera-Zarco & Marco Opazo-Basáez, 2022. "The emergent role of digital technologies in the context of humanitarian supply chains: a systematic literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1003-1044, December.
    8. Shivam Gupta & Sachin Modgil & Ajay Kumar & Uthayasankar Sivarajah & Zahir Irani, 2022. "Artificial intelligence and cloud-based Collaborative Platforms for Managing Disaster, extreme weather and emergency operations," Post-Print hal-04325638, HAL.

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