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Models of Everywhere Revisited: A Technological Perspective

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Models of Everywhere Revisited : A Technological Perspective. / Blair, Gordon; Beven, Keith; Lamb, Rob; Bassett, Richard; Cauwenberghs, Kris; Hankin, Barry; Dean, Graham; Hunter, Neil; Edwards, Liz; Nundloll, Vatsala; Samreen, Faiza; Simm, William; Towe, Ross.

In: Environmental Modelling and Software, Vol. 122, 104521, 01.12.2019.

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@article{75f615056d8247d3aaaab40d5088f78a,
title = "Models of Everywhere Revisited: A Technological Perspective",
abstract = "The concept {\textquoteleft}models of everywhere{\textquoteright} was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and non-linearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment.",
keywords = "environmental modelling, models of everywhere, grid computing, cloud computing, data science",
author = "Gordon Blair and Keith Beven and Rob Lamb and Richard Bassett and Kris Cauwenberghs and Barry Hankin and Graham Dean and Neil Hunter and Liz Edwards and Vatsala Nundloll and Faiza Samreen and William Simm and Ross Towe",
year = "2019",
month = dec
day = "1",
doi = "10.1016/j.envsoft.2019.104521",
language = "English",
volume = "122",
journal = "Environmental Modelling and Software",
issn = "1364-8152",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - Models of Everywhere Revisited

T2 - A Technological Perspective

AU - Blair, Gordon

AU - Beven, Keith

AU - Lamb, Rob

AU - Bassett, Richard

AU - Cauwenberghs, Kris

AU - Hankin, Barry

AU - Dean, Graham

AU - Hunter, Neil

AU - Edwards, Liz

AU - Nundloll, Vatsala

AU - Samreen, Faiza

AU - Simm, William

AU - Towe, Ross

PY - 2019/12/1

Y1 - 2019/12/1

N2 - The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and non-linearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment.

AB - The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and non-linearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment.

KW - environmental modelling

KW - models of everywhere

KW - grid computing

KW - cloud computing

KW - data science

U2 - 10.1016/j.envsoft.2019.104521

DO - 10.1016/j.envsoft.2019.104521

M3 - Journal article

VL - 122

JO - Environmental Modelling and Software

JF - Environmental Modelling and Software

SN - 1364-8152

M1 - 104521

ER -