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DAFNI: a computational platform to support infrastructure systems research

DAFNI: a computational platform to support infrastructure systems research
DAFNI: a computational platform to support infrastructure systems research

Research into the engineering of infrastructure systems is increasingly data intensive. Researchers build computational models to explore scenarios such as investigating the merits of infrastructure plans, analysing historical data to inform system operations or assessing the impacts of infrastructure on the environment. Models are more complex, at higher resolution and with larger coverage. Researchers also require a 'multi-systems' approach to explore interactions between systems, such as energy and water with urban development, and across scales, from buildings and streets to regions or nations. Consequently, researchers need enhanced computational resources to support cross-institutional collaboration and sharing at scale. The Data and Analytics Facility for National Infrastructure (DAFNI) is an emerging computational platform for infrastructure systems research. It provides high-throughput compute resources so larger data sets can be used, with a data repository to upload data and share these with collaborators. Users' models can also be uploaded and executed using modern containerisation techniques, giving platform independence, scaling and sharing. Further, models can be combined into workflows, supporting multi-systems modelling and generating visualisations to present results. DAFNI forms a central resource accessible to all infrastructure systems researchers in the UK, supporting collaboration and providing a legacy, keeping data and models available beyond the lifetime of a project.

data, digital twin, information technology, infrastructure planning, numerical modelling
108-116
Matthews, Brian
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Hall, Jim
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Batty, Michael
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Blainey, Simon
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Cassidy, Nigel
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Choudhary, Ruchi
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Coca, Daniel
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Hallett, Stephen
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Harou, Julien J
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James, Phil
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Lomax, Nik
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Oliver, Peter
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Sivakumar, Aruna
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Tryfonas, Theodoros
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Varga, Liz
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Matthews, Brian
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Hall, Jim
4613e0ec-942b-4ac0-ac58-77ec6a886cfc
Batty, Michael
44c7941f-7b1c-4c1c-b351-01ba03927f4c
Blainey, Simon
ee6198e5-1f89-4f9b-be8e-52cc10e8b3bb
Cassidy, Nigel
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Choudhary, Ruchi
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Coca, Daniel
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Hallett, Stephen
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Harou, Julien J
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James, Phil
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Lomax, Nik
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Oliver, Peter
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Sivakumar, Aruna
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Tryfonas, Theodoros
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Varga, Liz
39934bed-2454-41fc-a8c0-56504764d731

Matthews, Brian, Hall, Jim, Batty, Michael, Blainey, Simon, Cassidy, Nigel, Choudhary, Ruchi, Coca, Daniel, Hallett, Stephen, Harou, Julien J, James, Phil, Lomax, Nik, Oliver, Peter, Sivakumar, Aruna, Tryfonas, Theodoros and Varga, Liz (2023) DAFNI: a computational platform to support infrastructure systems research. Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction, 176 (3), 108-116. (doi:10.1680/jsmic.22.00007).

Record type: Article

Abstract

Research into the engineering of infrastructure systems is increasingly data intensive. Researchers build computational models to explore scenarios such as investigating the merits of infrastructure plans, analysing historical data to inform system operations or assessing the impacts of infrastructure on the environment. Models are more complex, at higher resolution and with larger coverage. Researchers also require a 'multi-systems' approach to explore interactions between systems, such as energy and water with urban development, and across scales, from buildings and streets to regions or nations. Consequently, researchers need enhanced computational resources to support cross-institutional collaboration and sharing at scale. The Data and Analytics Facility for National Infrastructure (DAFNI) is an emerging computational platform for infrastructure systems research. It provides high-throughput compute resources so larger data sets can be used, with a data repository to upload data and share these with collaborators. Users' models can also be uploaded and executed using modern containerisation techniques, giving platform independence, scaling and sharing. Further, models can be combined into workflows, supporting multi-systems modelling and generating visualisations to present results. DAFNI forms a central resource accessible to all infrastructure systems researchers in the UK, supporting collaboration and providing a legacy, keeping data and models available beyond the lifetime of a project.

Text
jsmic.22.00007 - Accepted Manuscript
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More information

Accepted/In Press date: 20 March 2023
e-pub ahead of print date: 14 April 2023
Additional Information: Publisher Copyright: © 2023 ICE Publishing. All rights reserved.
Keywords: data, digital twin, information technology, infrastructure planning, numerical modelling

Identifiers

Local EPrints ID: 479992
URI: http://eprints.soton.ac.uk/id/eprint/479992
PURE UUID: e1db256e-4973-42be-8e97-5d29ffbf39f0
ORCID for Simon Blainey: ORCID iD orcid.org/0000-0003-4249-8110

Catalogue record

Date deposited: 31 Jul 2023 17:04
Last modified: 18 Mar 2024 03:11

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Contributors

Author: Brian Matthews
Author: Jim Hall
Author: Michael Batty
Author: Simon Blainey ORCID iD
Author: Nigel Cassidy
Author: Ruchi Choudhary
Author: Daniel Coca
Author: Stephen Hallett
Author: Julien J Harou
Author: Phil James
Author: Nik Lomax
Author: Peter Oliver
Author: Aruna Sivakumar
Author: Theodoros Tryfonas
Author: Liz Varga

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