Provenance in scientific research involves documenting the history of data, focusing on the changes it undergoes and the relationships between various data points throughout its entire lifecycle. By capturing detailed information on how data is processed and transformed, provenance enables researchers to trace, validate and ensure the integrity of their results. This process becomes particularly crucial in complex workflows and high-performance computing environments, where managing intricate tasks and data relationships is essential for maintaining scientific rigor and fostering collaboration. This paper highlights the importance of supporting data reliability and traceability of scientific workflows, providing valuable insights and tools to tracking provenance in Workflow Management Systems.
Enabling Provenance Tracking in Workflow Management Systems / Sacco, Ludovica; Sopranzetti, Carolina; Fiore, Sandro. - (2024), pp. 4402-4409. ( 2024 IEEE International Conference on Big Data, BigData 2024 usa 2024) [10.1109/bigdata62323.2024.10825405].
Enabling Provenance Tracking in Workflow Management Systems
Sacco, Ludovica
;Fiore, Sandro
2024-01-01
Abstract
Provenance in scientific research involves documenting the history of data, focusing on the changes it undergoes and the relationships between various data points throughout its entire lifecycle. By capturing detailed information on how data is processed and transformed, provenance enables researchers to trace, validate and ensure the integrity of their results. This process becomes particularly crucial in complex workflows and high-performance computing environments, where managing intricate tasks and data relationships is essential for maintaining scientific rigor and fostering collaboration. This paper highlights the importance of supporting data reliability and traceability of scientific workflows, providing valuable insights and tools to tracking provenance in Workflow Management Systems.| File | Dimensione | Formato | |
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