Shared data, digital transition and value creation

With these you have realistic research outcomes, impact, exploitation, commercialization, knowledge valorisation. Without these you/project is less competitive.

Value chains can only optimize when data flows between their links. Your research outcome will have more impact if it considers how data from your work connects to the value chain.

The Digital Product Passport is a regulatory requirement. Any research output (material, process, product) to be in a market must align with DPP requirements.

Shared and verified data creates a realistic knowledge valorisation. Researchers who understand this can position their outcomes within emerging data economy frameworks.

Green and digital transition policy is structured around twin transition. Green outcomes require digital structuring.

Researchers may propose ML and AI optimizing. But ML and AI operate on data, and that data should align with value chain, or usefulness of ML/AI is limited. Those who are active with ML and AI have the opportunity to adapt and take position.

We have experience in shared data and value creation, including from our own pilot. This is why we created the Data-Driven Value Creation for European Research Impact and Exploitation. We share our experience, and participants interested to develop their cases can in addition learn from each other’s cases through an interactive workshop. This is available for MSCA researchers in ongoing projects, and 2026 MSCA PF applicants can include this in their plan.