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20192023
most citedWorkflow Provenance in the Lifecycle of Scientific Machine Learning

44 citations · 62 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.DB2023

A Polystore Architecture Using Knowledge Graphs to Support Queries on Heterogeneous Data Stores

Leonardo Guerreiro Azevedo, Renan Francisco Santos Souza, Elton F. de S. Soares +4

Modern applications commonly need to manage dataset types composed of heterogeneous data and schemas, making it difficult to access them in an integrated way. A single data store t…

cs.DB2023

ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud Continuum

Daniel Rosendo, Marta Mattoso, Alexandru Costan +4

Modern scientific workflows require hybrid infrastructures combining numerous decentralized resources on the IoT/Edge interconnected to Cloud/HPC systems (aka the Computing Continu…

cs.DB2020★ 44 cited

Workflow Provenance in the Lifecycle of Scientific Machine Learning

Renan Souza, Leonardo G. Azevedo, Vítor Lourenço +10

Machine Learning (ML) has already fundamentally changed several businesses. More recently, it has also been profoundly impacting the computational science and engineering domains,…

cs.DB2020

Managing Data Lineage of O&G Machine Learning Models: The Sweet Spot for Shale Use Case

Raphael Thiago, Renan Souza, L. Azevedo +7

Machine Learning (ML) has increased its role, becoming essential in several industries. However, questions around training data lineage, such as "where has the dataset used to trai…

cs.DB2019★ 13 cited

Keeping Track of User Steering Actions in Dynamic Workflows

Renan Souza, Vítor Silva, José Camata +3

In long-lasting scientific workflow executions in HPC machines, computational scientists (the users in this work) often need to fine-tune several workflow parameters. These tunings…