With Quantinar, a P2P knowledge platform, we are tapping the important elements of the information age where the power of data and statistics has never been more prevalent. Academics, architects, medical doctors, journalists, lawyers, programmers and many other professionals nowadays require an accurate application of statistical methods. Instead many branches are subject to a crisis of integrity, which is shown in improper use of statistical models, p-hacking, HARKing or failure to replicate results. The first goal is to conduct basic qualitative and explorative work for the subsequent data collection and analysis. This leads to the results of task 2, that provides a suitable technical infrastructure that is used to securely record, process and make available scientifically and practically the multitude of different project data. Finally, criteria how to evaluate, e.g., lending platforms, NFT platforms and other DeFi-related projects will be identified using both quantitative and qualitative inputs and methods with different degree of formalization (e.g., from judgmental forecasting, drawing on the insight of experienced stakeholders, to formal Machine Learning (ML) classifiers). Insights from diverse sources of information and methods will be blended using newly developed ML tools, like expectile clustering.