MRT is modernising its research environment to accelerate the development of new materials. Even today, this field still relies heavily on empirical approaches and data from multiple experiments, often scattered across independent silos and stored in highly heterogeneous formats. This fragmentation makes it complex and time-consuming to use the data, and ill-suited to the growing needs of research teams.
Faced with these limitations, MRT has embarked on a profound transformation of its data management. The aim is to simplify access to information, improve the reliability of analyses and create a common foundation capable of supporting scientific innovation. To achieve this, the entire data lifecycle is structured according to FAIR principles, ensuring that information is easy to find, accessible, interoperable and reusable at every stage of the research process.
This approach involves setting up a unified data infrastructure designed to collect and harmonise data from the various experimental phases. A centralised data pipeline automatically gathers information, transforms it and standardises it to ensure consistency. This architecture offers great flexibility: new data sources can be easily integrated, gradually enriching a common and sustainable knowledge base.
Thanks to this organisation, research teams have reliable and rapid access to all experimental data. Manual and repetitive tasks are reduced, freeing up time for scientific analysis and interpretation. The data can thus be directly exploited by modern tools, in particular machine learning algorithms, paving the way for more predictive approaches and a significant acceleration of materials research.
By structuring and making data fully accessible, MRT transforms it into a real lever for innovation. This infrastructure lays the foundations for more agile, collaborative research that is resolutely focused on the scientific methods of tomorrow.
