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Data-driven decisions for flood risk management

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Data-driven decisions for flood risk management. / Edwards, Elizabeth Ruth; Mullagh, Louise; Towe, Ross Paul; Nundloll, Vatsala; Dean, Claire; Dean, Graham; Simm, William Alexander; Samreen, Faiza; Bassett, Richard; Blair, Gordon Shaw.

Data for Policy 2017: Government by Algorithm?. Data for Policy, 2017.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

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@inproceedings{f624debdaac2435cb77decec9e9bf1b7,
title = "Data-driven decisions for flood risk management",
abstract = "Ensemble is an interdisciplinary research team, working to explore the opportunity of new and emergent digital technologies in understanding, mitigating and adapting to environmental change. Using methods drawn from computer science, environmental science, social science, statistics, art, design and writing the team aim to transform the work of environmental scientists and decision makers, and the experience of communities by addressing themes related to complexity, uncertainty and abstraction of data. This paper discusses activities undertaken within a research ‘sprint’ directed at addressing flood risk management through data driven decision making, communication and community engagement.",
author = "Edwards, {Elizabeth Ruth} and Louise Mullagh and Towe, {Ross Paul} and Vatsala Nundloll and Claire Dean and Graham Dean and Simm, {William Alexander} and Faiza Samreen and Richard Bassett and Blair, {Gordon Shaw}",
year = "2017",
month = "9",
day = "6",
doi = "10.5281/zenodo.884180",
language = "English",
booktitle = "Data for Policy 2017",
publisher = "Data for Policy",

}

RIS

TY - GEN

T1 - Data-driven decisions for flood risk management

AU - Edwards, Elizabeth Ruth

AU - Mullagh, Louise

AU - Towe, Ross Paul

AU - Nundloll, Vatsala

AU - Dean, Claire

AU - Dean, Graham

AU - Simm, William Alexander

AU - Samreen, Faiza

AU - Bassett, Richard

AU - Blair, Gordon Shaw

PY - 2017/9/6

Y1 - 2017/9/6

N2 - Ensemble is an interdisciplinary research team, working to explore the opportunity of new and emergent digital technologies in understanding, mitigating and adapting to environmental change. Using methods drawn from computer science, environmental science, social science, statistics, art, design and writing the team aim to transform the work of environmental scientists and decision makers, and the experience of communities by addressing themes related to complexity, uncertainty and abstraction of data. This paper discusses activities undertaken within a research ‘sprint’ directed at addressing flood risk management through data driven decision making, communication and community engagement.

AB - Ensemble is an interdisciplinary research team, working to explore the opportunity of new and emergent digital technologies in understanding, mitigating and adapting to environmental change. Using methods drawn from computer science, environmental science, social science, statistics, art, design and writing the team aim to transform the work of environmental scientists and decision makers, and the experience of communities by addressing themes related to complexity, uncertainty and abstraction of data. This paper discusses activities undertaken within a research ‘sprint’ directed at addressing flood risk management through data driven decision making, communication and community engagement.

U2 - 10.5281/zenodo.884180

DO - 10.5281/zenodo.884180

M3 - Conference contribution/Paper

BT - Data for Policy 2017

PB - Data for Policy

ER -