The Framework to Advance Climate, Economic, and Impact Investigations with Information Technology (FACE-IT) is a workflow engine and data science portal based on Galaxy and Globus technologies that enables computational scientists to integrate data, pre/post processing and simulation into a framework that supports offline environmental model coupling. We describe how the FACE-IT workflows engine can be used to couple many simulation/prediction models, leveraging high-performance cloud computing resources to enable fast full system modeling and produce operational predictions about the impact of pollutants spilled out from both natural and anthropic sources in mussels farming high density areas. Mussel farms product quality remains a challenging problem for operational marine science: in this scenario, the model chain presented in this work, orchestrated in a workflow fashion, produces a huge amount of predicted spatially-referenced (big) data. The software infrastructure we built using FACE-IT Galaxy Globus provides tools enabled to evaluate the impact of hazardous substances (chemical or biological) continuously or spottily spilled in the marine environment.

Using the FACE-IT portal and workflow engine for operational food quality prediction and assessment: An application to mussel farms monitoring in the Bay of Napoli, Italy

Montella, Raffaele
;
Di Luccio, Diana;Riccio, Angelo;
2020-01-01

Abstract

The Framework to Advance Climate, Economic, and Impact Investigations with Information Technology (FACE-IT) is a workflow engine and data science portal based on Galaxy and Globus technologies that enables computational scientists to integrate data, pre/post processing and simulation into a framework that supports offline environmental model coupling. We describe how the FACE-IT workflows engine can be used to couple many simulation/prediction models, leveraging high-performance cloud computing resources to enable fast full system modeling and produce operational predictions about the impact of pollutants spilled out from both natural and anthropic sources in mussels farming high density areas. Mussel farms product quality remains a challenging problem for operational marine science: in this scenario, the model chain presented in this work, orchestrated in a workflow fashion, produces a huge amount of predicted spatially-referenced (big) data. The software infrastructure we built using FACE-IT Galaxy Globus provides tools enabled to evaluate the impact of hazardous substances (chemical or biological) continuously or spottily spilled in the marine environment.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/66741
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