Models in the Cloud: Exploring Next Generation Environmental Software Systems

SAMREEN, Faiza, SIMM, Will, BLAIR, Gordon, BASSETT, Richard and YOUNG, Paul (2020). Models in the Cloud: Exploring Next Generation Environmental Software Systems. In: Environmental Software Systems. Data Science in Action. IFIP Advances in Information and Communication Technology . Springer, Cham.

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Official URL: https://link.springer.com/chapter/10.1007%2F978-3-...
Open Access URL: https://link.springer.com/chapter/10.1007%2F978-3-...
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    Abstract

    There is growing interest in the application of the latest trends in computing and data science methods to improve environmental science. However we found the penetration of best practice from computing domains such as software engineering and cloud computing into supporting every day environmental science to be poor. We take from this work a real need to re-evaluate the complexity of software tools and bring these to the right level of abstraction for environmental scientists to be able to leverage the latest developments in computing. In the Models in the Cloud project, we look at the role of model driven engineering, software frameworks and cloud computing in achieving this abstraction. As a case study we deployed a complex weather model to the cloud and developed a collaborative notebook interface for orchestrating the deployment and analysis of results. We navigate relatively poor support for complex high performance computing in the cloud to develop abstractions from complexity in cloud deployment and model configuration. We found great potential in cloud computing to transform science by enabling models to leverage elastic, flexible computing infrastructure and support new ways to deliver collaborative and open science.

    Item Type: Book Section
    Additional Information: 13th IFIP WG 5.11 International Symposium, ISESS 2020, Wageningen, The Netherlands, February 5–7, 2020, Proceedings
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 01 May 2020 11:16
    Last Modified: 19 Jun 2020 15:52
    URI: http://shura.shu.ac.uk/id/eprint/26221

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