Quantinar: A blockchain peer-to-peer ecosystem for modern data analytics

• Main Authors: BAG, Raul, SPILAK, Bruno, WINKEL, Julian, HARDLE, Wolfgang Karl
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Blockchain; Machine learning; dao; p2p; e-Learning; Data Science
• Online Access: https://ink.library.smu.edu.sg/skbi/45; https://ink.library.smu.edu.sg/context/skbi/article/1044/viewcontent/s00180_024_01529_7.pdf
• Institution: Singapore Management University

The power of data and correct statistical analysis has never been more prevalent. Academics and practitioners require nowadays an accurate application of quantitative methods. Yet many branches are subject to a crisis of integrity, which is shown in an improper use of statistical models, p-hacking, HARKing, or failure to replicate results. We propose the use of a Peer-to-Peer (P2P) ecosystem based on a blockchain network, Quantinar, to support quantitative analytics knowledge paired with code in the form of Quantlets or software snippets. The integration of blockchain technology allows Quantinar to ensure fully transparent and reproducible scientific research.