Home > Research > Publications & Outputs > Rethinking data-driven decision support in floo...

Electronic data

  • FloodRisk_DecisionSupport (PRE-PRINT)

    Rights statement: 12m

    Accepted author manuscript, 4.26 MB, PDF document

    Embargo ends: 1/01/50

    Available under license: CC BY

View graph of relations

Rethinking data-driven decision support in flood risk management for a big data age

Research output: Contribution to journalJournal article

Forthcoming
<mark>Journal publication date</mark>6/07/2020
<mark>Journal</mark>Journal of Flood Risk Management
Publication statusAccepted/In press
Original languageEnglish

Abstract

Decision-making in flood risk management is increasingly dependent on access to data, with the availability of data increasing dramatically in recent years. We are therefore moving towards an era of big data, with the added challenges that, in this area, data sources are highly heterogeneous, at a variety of scales, and include a mix of structured and unstructured data. The key requirement is therefore one of integration and subsequent analyses of this complex web of data. This paper examines the potential of a data-driven approach to support decision-making in flood risk management, with the goal of investigating a suitable software architecture and associated set of techniques to support a more data-centric approach. The key contribution of the paper is a cloud-based data hypercube that achieves the desired level of integration of highly complex data. This hypercube builds on innovations in cloud services for data storage, semantic enrichment and querying, and also features the use of notebook technologies to support open and collaborative scenario analyses in support of decision making. The paper also highlights the success of our agile methodology in weaving together cross-disciplinary perspectives and in engaging a wide range of stakeholders in exploring possible technological futures for flood risk management.