Work

Computational Reproducibility Validation in Cloud Big Data Pipelines Through Provenance and Machine Learning

Year: 2026

Type: article

Abstract: This deposit contains all artefacts required to reproduce the experimental results reported in the paper titled as : *Computational Reproducibility and Provenance in Cloud-Based Climate Data Applications*. The work proposes and validates a three-layer computational reproducibility scoring framework that uses provenance metadata and machine learning to assess whether a scientific workflow can be reliably reproduced across different cloud platforms.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.19254677

Author: AL-Sammak, Shirin

Language: English

Topic: Scientific Computing and Data Management

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W7141643076

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