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Preserving File Provenance Using Principles of Blockchain to Ensure Scientific Reproducibility

Reproducibility plays an essential role in scientific research to ensure accuracy and serves as a foundation for future advancements. Scientific reproducibility becomes particularly challenging when dealing with vast amounts of input files that change hands or move across different laboratories or o...

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Main Authors:	Hasan, Rizbanul, Purawat, Shweta, Olschanowsky, Catherine, Altintas, Ilkay
Format:	Conference Proceeding
Language:	English
Subjects:	blockchain Blockchains Data integrity data provenance Laboratories metadata Organizations Reliability reproducibility Reproducibility of results scientific workflow
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creator	Hasan, Rizbanul Purawat, Shweta Olschanowsky, Catherine Altintas, Ilkay
description	Reproducibility plays an essential role in scientific research to ensure accuracy and serves as a foundation for future advancements. Scientific reproducibility becomes particularly challenging when dealing with vast amounts of input files that change hands or move across different laboratories or organizations. Preserving the provenance of data files ensures critical information about the originality of data files is captured to support the reproducibility of scientific research. The paper focuses on capturing and verifying input and output data file provenance using the principles of blockchain. The technique stores the hashes of data files in a database along with user and workflow information. It allows the workflow to verify the data against the hashes at any point. The method is demonstrated using Parflow, a Hydrologic model, as a proof-of-concept.
doi_str_mv	10.1109/e-Science58273.2023.10254665
format	conference_proceeding
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source	IEEE Xplore All Conference Series
subjects	blockchain Blockchains Data integrity data provenance Laboratories metadata Organizations Reliability reproducibility Reproducibility of results scientific workflow
title	Preserving File Provenance Using Principles of Blockchain to Ensure Scientific Reproducibility
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