DAFNI: A computational platform to support infrastructure systems research

  • Brian Matthews*
  • , Jim Hall
  • , Michael Batty
  • , Simon Blainey
  • , Nigel Cassidy
  • , Ruchi Choudhary
  • , Daniel Coca
  • , Stephen Hallett
  • , Julien J. Harou
  • , Phil James
  • , Nik Lomax
  • , Peter Oliver
  • , Aruna Sivakumar
  • , Theodoros Tryfonas
  • , Liz Varga
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)108-116
Number of pages9
JournalProceedings of the Institution of Civil Engineers: Smart Infrastructure and Construction
Volume176
Issue number3
Early online date20 Mar 2023
DOIs
Publication statusPublished - Sept 2023

Bibliographical note

Publisher Copyright:
© 2023 Emerald Publishing Limited: All rights reserved.

Keywords

  • data
  • digital twin
  • information technology
  • infrastructure planning
  • numerical modelling

ASJC Scopus subject areas

  • Information Systems
  • Civil and Structural Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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