4 V Challenge

Materials science is entering an era where the growth of data from experiments and simulations is expanding beyond a level that is properly processable by established scientific methods. At several MPIs of the Section for Chemistry, Physics, and Technology (CPTS), the so-called “4 V challenge” is becoming eminent: - Volume (the amount of data)- Variety (the heterogeneity of form and meaning of data)- Velocity (the rate at which data may change or new data arrive)- Veracity (uncertainty of quality) This exploitation requires new and dedicated technology based on approaches in statistical and machine learning, compressed sensing, and other recent technologies from mathematics, computer science, statistics and information technology. The PIs of the proposed MaxNet cover a significant breadth in research areas, and they are convinced that the envisioned synergy will enable them and their MPIs to develop novel, domain-specific and property-specific methods to enter and shape the era of data-driven materials research. The goal of the proposed MaxNet is to fully exploit these scientific potentials of materials science activities of the CPTS and to raise the consortium to world leadership in data-driven materials science.