Virtually every new commercial product, be they smart phones, solar cells, batteries, transport technology, artificial hips, etc., depends on improved or even novel materials, which makes materials discovery highly relevant for research and industry. Computational materials science is an increasingly influential method to identify such critical materials for industrial R&D. Enormous amounts of data, precious but heterogeneous and as such difficult to access and utilize, are already stored in repositories scattered across Europe.
The Novel Materials Discovery (NOMAD) Laboratory [1] was recently founded by a team of computational materials science groups with complementary expertise, and a few high-performance computing centers, to open new HPC opportunities by enabling data access and delivering powerful new tools to search, retrieve and manage it. The objectives of this European Center of Excellence (CoE) include the creation of a materials encyclopedia, and the development of big-data analytics and advanced graphics tools for materials science and engineering. Those goals are complementary with those of the other two CoEs supported by the European Comission and active in the field of CECAM activities (E-cam [2] and Max [3]). The NOMAD Researchers are currently creating a large, homogenised materials database, as well as the analytical tools and code developments necessary to extract information from it. We are confident that the available HPC infrastructure and the envisaged developments will contribute to the discovery of new scientific phenomena, novel devices, and advances in materials science and engineering. An essential corner stone of the project is is the NOMAD Repository [4] which contains the produced data and records the input and output files of many high-quality calculations performed fellow researchers working all over the world. The Repository is unique in the sense that it is not restricted to one or a few simulation programs ("codes") but it accepts output from all important codes. As of early July 2016, it contains results from more than three million different calculations, corresponding to billions of CPU-core hours used on several high-performance computers all over the planet. Recently, there has been a very significant growth of industrial interest (from large companies as well as SMEs) in computational materials science, motivated by the innovation potential of new materials and improved existing materials. However, the scientific complexity of the topic and the heterogeneous and fragmented nature of the research field make it difficult to translate research leadership into accomplished innovation.

Thus, it is particularly important at this point in time to bring materials modelling closer to industrial/societal exploitation in real terms. We strive to establish among EU-based industries full awareness of the extent to which the wealth of newly available data could boost their competitiveness. To raise industrial interest, the potential of big-data activities to foster industrial business will have to be made apparent in practical terms. We believe that this requires close engagement with industries already at the tool design level. We are also convinced that workshops with industry representatives are important (in fact, indispensable) venues to gather industrial feedback on their plans and needs concerning materials data, and to inform/train industry representatives on tool-usage for industrial R&D users. The workshop proposed here will accomplish both of these goals.