We are witnessing a dramatic increase of large engineering data resource availability and accessibility.
Data-driven technologies, sensors connected through the Internet of Things (IoT) and big data capabilities nowadays show sustained development throughout an industrial product’s lifecycle, from R&D testing to design, verification, production validation and maintenance.
Such progress in modern industrial environments exposes richer, domain-specific data and requires validated model-driven processes that interact dynamically with data science and computational modelling approaches. New research in aggregation, integration, analysis and governance of data and derived models is now required throughout the lifecycle of industrial products - from design to exploitation, reuse, and recycle.
Delivering on these new opportunities requires development, validation and adoption of effective data science solutions that can provide information and insight from data and models to applications of cyber-physical systems, from autonomous cars to industrial processes.