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Dafni: a computational platform to support infrastructure systems research

Lookup NU author(s): Professor Daniel Coca, Professor Philip James

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Abstract

© 2023 ICE Publishing. All rights reserved. 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 it 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 a project's lifetime.

Publication metadata

Author(s): Matthews B, Hall J, Batty M, Blainey S, Cassidy N, Choudhary R, Coca D, Hallett S, Harou JJ, James P, Lomax N, Oliver P, Sivakumar A, Tryfonas T, Varga L

Publication type: Article

Publication status: Published

Journal: Proceedings of the Institution of Civil Engineers: Smart Infrastructure and Construction

Year: 2023

Volume: 176

Issue: 3

Pages: 108-116

Print publication date: 01/09/2023

Online publication date: 14/04/2023

Acceptance date: 20/01/2023

ISSN (electronic): 2397-8759

Publisher: ICE Publishing

URL: https://doi.org/10.1680/jsmic.22.00007

DOI: 10.1680/jsmic.22.00007

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