Sharing of biomolecular MD simulation and other data is becoming increasingly important in the age of big data and artificial intelligence . Besides the data itself, also programmatic access is a necessary requirement for data-driven and machine learning applications. This is particularly challenging when field-specific smart guidelines and community-consensus bestpractices have not yet been defined, which is the case in biomolecular simulations . The NMRlipids Databank demonstrates how these issues can be solved by the overlay databank design, where the raw data are distributed to already publicly available decentralized locations, while the core of the databank is composed only of the metadata stored in a version-controlled git repository with an open-access license. On the other hand, the open-collaboration approach developed in the NMRlipids Project creates incentives for sharing the data by offering authorship in published articles to the contributors. Advantages of such an approach are demonstrated here for membrane simulations, yet the concept can be applied to any other biomolecules, as well as in any other field where similar barriers hinder the AI revolution, such as the assignment of NMR spectra .