Towards decentralized science : evaluating the data provenance of blockchain-enabled cameras

Abstract

The proliferation of digital technologies and the increasing importance of data in scientific research necessitate new approaches to data integrity, transparency and decentralization. This dissertation, titled "Towards Decentralized Science: Evaluating the Data Provenance of Blockchain-Enabled Cameras," explores innovative solutions for enhancing scientific image data provenance through the integration of blockchain technology, guided by the research question: "What specific blockchain-based implementations can enhance the secure capture, storage and content verification of digital images, and how can these developments contribute to the advancement of decentralized science?" This research leverages both Bitcoin and Ethereum blockchain implementations tailored to address the intricacies of securing data provenance. By examining these implementations, I aim to elucidate their unique contributions to bolstering the security and trustworthiness of digital images. My research not only sheds light on theoretical considerations but also emphasizes the practical aspects of implementation, providing a comprehensive understanding of the prospects and challenges involved. The evolving landscape of open science and the increasing demand for data reproducibility and open access act as catalysts for our exploration. This study situates itself at the intersection of blockchain technology and scientific research practices, aiming to bridge the gap between the burgeoning need for trust in digital data and the decentralized ethos of contemporary scientific endeavors. In summary, this dissertation seeks to contribute to the discourse on Decentralized Science by proposing tangible solutions to the challenges surrounding the secure capture, storage and content verification of digital images. Through an in-depth analysis of various blockchain implementations, I aspire to provide a pathway for researchers and technologists to navigate the complexities of immutable data provenance of digital images in the pursuit of transparent, reproducible and open scientific practices.