Home > Research > Publications & Outputs > SE in ES

Electronic data

  • icse_seis_2018_ACTIVE-9

    Rights statement: © 2018 Copyright held by the owner/author(s). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ICSE-SEIS '18 Proceedings of the 40th International Conference on Software Engineering http://dx.doi.org/10.1145/3183428.3183430

    Accepted author manuscript, 619 KB, PDF document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License

Links

Text available via DOI:

View graph of relations

SE in ES: Opportunities for Software Engineering and Cloud Computing in Environmental Science

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date3/06/2018
Host publicationICSE-SEIS '18 Proceedings of the 40th International Conference on Software Engineering: Software Engineering in Society
Place of PublicationNew York
PublisherACM
Pages61-70
Number of pages10
ISBN (print)9781450356619
<mark>Original language</mark>English

Abstract

New and emergent computing architectures and software engineering practices provide an opportunity for environmental models to be deployed more efficiently and democratically. In this paper we aim to capture the software engineering practices of environmental scientists, highlight opportunities for software engineering and work towards developing a domain specific language for the configuration and deployment of environmental models. We hold a series of interviews with environmental scientists involved in developing and deploying computer based environmental models about the approach taken in engineering models, and describe a case study in deploying an environmental model (WRF: Weather Research & Forecasting) on a cloud architecture. From these studies we find a number of opportunities for a) software engineering methods and tools such as Domain Specific Languages to play a role in abstracting from underlying computing complexity, and for b) new architectures to increase efficiency and availability of deployment. Together, we propose they will allow scientists to concentrate on fundamental science rather than specifics of the underlying computing.

Bibliographic note

© 2018 Copyright held by the owner/author(s). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ICSE-SEIS '18 Proceedings of the 40th International Conference on Software Engineering http://dx.doi.org/10.1145/3183428.3183430