Ten institutions of the Max Planck Society and Humboldt-Universität zu Berlin combine their know-how in data-driven materials science. The aim is a better use of the possibilities associated with analyzing large amounts of data. Which alloying constituents lend a steel unique bending strength, extreme hardness and non-rusting properties? Are semiconductors that promise greater efficiencies for solar modules available, and do they offer greater flexibility than silicon? What would be the best catalyst for a very specific chemical reaction? Or, how should a surface be coated to achieve the best possible thermal protection? To more easily find answers to these typical problems facing materials scientist in future, researchers from the above cited Institutions hope to better exploit the opportunities presented by analyzing large volumes of data. To this end, they cooperate in MaxNet on Big-Data-Driven Materials Science or, simply, BiGmax.