Optimizing Governance In Blockchain Open-Source Software: Trends and Insights Across The GitHub Timeline

GitHub is a web platform that enables programmers to share their code to fellow developers, facilitating seamless collaboration. Many GitHub projects are open-source software (OSS), whose source code is readily available to the public. OSS is essential to decentralization in blockchain, fostering innovation towards more resilient and secure blockchains by shifting control from a central entity to a distributed network. These projects utilize a wide variety of funding sources and governance models. This study aims to investigate activity on such projects and find trends with their respective funding and governance models. Our data was found on GitHub Archive, a project that streams and archives public events on GitHub such as issues, logins, or commits. We first ran an SQL script to access all of the GitHub activities for 600+ OSS projects. This script was run on BigQuery, a Google Cloud platform utilizing Google’s powerful processing infrastructure to gather data at high speeds, convenient for large-scale data collection of millions of records. Next, our team conducted thorough research on these projects and the organizations that governed them, recording key details such as their funding, governance, and associated cryptocurrencies. An analysis of a smaller set of data showed that projects governed by non-profits were typically funded by crypto token sales or crowdfunding/donations. This suggests that some trend(s) indeed may exist between funding, governance, and GitHub activity. By comparing these key details with the frequency of various GitHub events, this analysis can provide unique insights into the operational frameworks that yield the most success for various organizations within the blockchain ecosystem. This abstract is part of a collection in which the overarching large project under Dr. Jiasun Li was subdivided into discrete critical tasks that were carried out by multiple individuals or smaller teams. Abstracts in this collection read similarly given the shared project goals, but represent distinct tasks completed by the abstract authors towards finalizing the described analysis.