Publication Date

5-2023

Date of Final Oral Examination (Defense)

3-6-2023

Type of Culminating Activity

Thesis

Degree Title

Master of Science in Computer Science

Department

Computer Science

Major Advisor

Catherine Olschanowsky, Ph.D.

Advisor

Alejandro Flores, Ph.D.

Advisor

Nasir Eisty, Ph.D.

Advisor

Shweta Purawat

Abstract

Reproducibility is essential in scientific research to ensure that any findings or conclusions are accurate. The reproducibility crisis around scientific studies and experiments is a significant concern. Several strategies and technologies have been introduced to share and exchange research data. However, very few address scientific reproducibility issues when interacting with vast amounts of data that may be manually altered during workflow execution.

This research focuses on verifying data provenance using the principles of blockchain. This technique stores the hashes of research data in a database along with user information. It allows the workflow to verify the data against the hashes at any point. The method is demonstrated using HydroFrame as a proof-of-concept.

DOI

https://doi.org/10.18122/td.2050.boisestate

Available for download on Sunday, July 06, 2025

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