Date of Final Oral Examination (Defense)
Type of Culminating Activity
Master of Science in Computer Science
Catherine Olschanowsky, Ph.D.
Alejandro Flores, Ph.D.
Nasir Eisty, Ph.D.
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.
Hasan, Rizbanul, "Verifying Data Provenance During Workflow Execution for Scientific Reproducibility" (2023). Boise State University Theses and Dissertations. 2050.
Available for download on Sunday, July 06, 2025