There is a large unexploited potential for data reuse within materials. Although digitalisation has got a lot of attention in recent years, the situation within materials research is still that data and knowledge resources are scattered, unstructured and with various levels of quality, which make reuse difficult. The main reason for this is that the materials community consists of a vast number of disciplines and groups using their own nomenclature and with little tradition of data sharing. Data often is not or poorly digitalised (e.g. results stored in Excel) and reaching FAIR data is further complicated by a lack of widely adopted common standards for data and metadata.
In this session we will discuss and share approaches for sharing data across disciplinary and community boundaries in an interoperable way to reach the goals of the green digital transformation requires integrating data across disciplines including environmental and social sustainability bridging innovation markets and value chains.
Computational Chemistry: An Industrial Perspective
by Misbah Sarwar (Johnson Matthey, UK)
Measure what’s easy to measure, calculate what’s easy to calculate, use AI to fill in gaps
by Felix Hanke (Biovia R&D, Dassault Systems UK Limited , UK)
Digitalization of materials processing: the case of battery manufacturing
by Alejandro Franco (Université de Picardie Jules Verne, FR)
