NoTamperData is a project designed to strengthen trust in primary research data. At the point of data collection, cryptographic fingerprints (hashes) of the raw dataset are securely stored online. This allows researchers to later prove that a specific dataset (e.g., a .csv file) is the authentic version collected at that time and has not been altered. If the raw dataset is preserved, its integrity can be verified against the stored fingerprint. Additionally, researchers can extend this assurance by sharing their data processing and analysis code, ensuring transparency and reproducibility throughout the research process. This project was inspired by a series of highly publicised research fraud cases in 2023, including that of Francesca Gino and Marc Tessier-Lavigne. After winning an “idea pitch competition” during ETH CC 2024 in Brussels, Simon partnered up with my John Ndigirigi to apply for a grant to continue building this infrastructure.