SELVEDAS: A Data and Compute as a Service Workflow Demonstrator targeting Supercomputing Ecosystems

Leong, Siew Hoon; Stadler, Hans-Christian; Chang, Mei-Chih; Dorsch, Juan Pablo; Aliaga, Tomas; Ashton, Alun

doi:10.1109/supercompcloud51944.2020.00007

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…Klampanos et al describe the implementation of an information registry prototype to demonstrate how it can enable collaboration and ensure consistency across the distributed infrastructure for Dispel and dispel4py [19]. Leong et al present the implementation of three use cases to demonstrate the feasibility and benefits of applying a cloud driven approach to supercomputing ecosystems [20] for large scale experimental facilities.…”

Section: Related Workmentioning

confidence: 99%

Designing a data infrastructure for catalysis science aligned to FAIR data principles

Hidalga

Goodall

Anyika

et al. 2022

Catalysis Communications

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Section: Related Workmentioning

confidence: 99%

Designing a data infrastructure for catalysis science aligned to FAIR data principles

Hidalga

Goodall

Anyika

et al. 2022

Catalysis Communications

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“…Klampanos et al describe the implementation of an information registry prototype to demonstrate how it can enable collaboration and ensure consistency across the distributed infrastructure for Dispel and dispel4py [23]. Leong et al present the implementation of three use cases to demonstrate the feasibility and benefits of applying a cloud driven approach to supercomputing ecosystems [25] for large scale experimental facilities.…”

Section: Related Workmentioning

confidence: 99%

A Workflow Demonstrator for Processing Catalysis Research Data

Hidalga

Decarolis

et al. 2022

Data Intelligence

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The UK Catalysis Hub (UKCH) is designing a virtual research environment to support data processing and analysis, the Catalysis Research Workbench (CRW). The development of this platform requires identifying the processing and analysis needs of the UKCH members and mapping them to potential solutions. This paper presents a proposal for a demonstrator to analyse the use of scientific workflows for large scale data processing. The demonstrator provides a concrete target to promote further discussion of the processing and analysis needs of the UKCH community. In this paper, we will discuss the main requirements for data processing elicited and the proposed adaptations that will be incorporated in the design of the CRW and how to integrate the proposed solutions with existing practices of the UKCH. The demonstrator has been used in discussion with researchers and in presentations to the UKCH community, generating increased interest and motivating further development.

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