Computational modelling for decision-making: where, why, what, who and how. Calder, M., Craig, C., Culley, D., de Cani, R., Donnelly, C. A., Douglas, R., Edmonds, B., Gascoigne, J., Gilbert, N., Hargrove, C., Hinds, D., Lane, D. C., Mitchell, D., Pavey, G., Robertson, D., Rosewell, B., Sherwin, S., Walport, M., & Wilson, A. 2018. ![Computational modelling for decision-making: where, why, what, who and how [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex In order to deal with an increasingly complex world, we need ever more sophisticated computational models that can help us make decisions wisely and understand the potential consequences of choices. But creating a model requires far more than just raw data and technical skills: it requires a close collaboration between model commissioners, developers, users and reviewers. Good modelling requires its users and commissioners to understand more about the whole process, including the different kinds of purpose a model can have and the different technical bases. This paper offers a guide to the process of commissioning, developing and deploying models across a wide range of domains from public policy to science and engineering. It provides two checklists to help potential modellers, commissioners and users ensure they have considered the most significant factors that will determine success. We conclude there is a need to reinforce modelling as a discipline, so that misconstruction is less likely; to increase understanding of modelling in all domains, so that the misuse of models is reduced; and to bring commissioners closer to modelling, so that the results are more useful
@article{calder_computational_2018,
title = {Computational modelling for decision-making: where, why, what, who and how},
shorttitle = {Computational modelling for decision-making},
url = {https://core.ac.uk/display/158977036?recSetID=},
doi = {10/gd6gmr},
abstract = {In order to deal with an increasingly complex world, we need ever more sophisticated computational models that can help us make decisions wisely and understand the potential consequences of choices. But creating a model requires far more than just raw data and technical skills: it requires a close collaboration between model commissioners, developers, users and reviewers. Good modelling requires its users and commissioners to understand more about the whole process, including the different kinds of purpose a model can have and the different technical bases. This paper offers a guide to the process of commissioning, developing and deploying models across a wide range of domains from public policy to science and engineering. It provides two checklists to help potential modellers, commissioners and users ensure they have considered the most significant factors that will determine success. We conclude there is a need to reinforce modelling as a discipline, so that misconstruction is less likely; to increase understanding of modelling in all domains, so that the misuse of models is reduced; and to bring commissioners closer to modelling, so that the results are more useful},
language = {en-gb},
urldate = {2021-01-28},
author = {Calder, Muffy and Craig, Claire and Culley, Dave and de Cani, Richard and Donnelly, Christl A. and Douglas, Rowan and Edmonds, Bruce and Gascoigne, Jonathon and Gilbert, Nigel and Hargrove, Caroline and Hinds, Derwen and Lane, David C. and Mitchell, Dervilla and Pavey, Giles and Robertson, David and Rosewell, Bridget and Sherwin, Spencer and Walport, Mark and Wilson, Alan},
year = {2018},
}
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