DARE Platform a Developer-Friendly and Self-Optimising Workflows-as-a-Service Framework for e-Science on the Cloud

Iraklis A. Klampanos, Chrysoula Themeli, Alessandro Spinuso, Rosa Filgueira, Malcolm Atkinson, André Gemünd, Vangelis Karkaletsis

Research output: Contribution to journalArticlepeer-review

Abstract

In recent years, science has relied more than ever on large-scale data as well as on distributed computing and human resources. Scientists and research engineers in fields such as climate science and computational seismology, constantly strive to make good use of remote and largely heterogeneous computing resources (HPC, Cloud, institutional or local resources, etc.), process, archive and analyse results stored in different locations and collaborate effectively with other scientists.

The DARE platform enables the seamless development and reusability of scientific workflows and applications, and the reproducibility of the experiments. Further, it provides Workflow-as-a-Service (WaaS) functionality and dynamic loading of execution contexts in order to hide technical complexity from its end users. This paper introduces the software implementing the DARE platform. More information on the H2020 DARE project is provided in Klampanos et al. (2019), Atkinson et al. (2019), and Atkinson et al. (2020).
Original languageEnglish
Article number2664
Number of pages4
JournalThe Journal of Open Source Software
Volume5
Issue number54
DOIs
Publication statusPublished - 17 Oct 2020

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