Technology Platform: Material Data Science
Why?
Modern materials science generates vast and diverse data—from atomic-scale simulations to processing experiments. To make meaningful use of this data, we need methods to manage, analyze, and link it across disciplines. The MDS Platform addresses this need by creating tools, workflows, and collaborations that turn data into knowledge and drive innovation.
What?
The Material Data Science (MDS) Platform connects materials research with data-driven approaches to accelerate discovery, design, and development. It focuses on integrating experimental data, simulations, and machine learning to extract insights from complex materials systems.
How?
- Developing and applying AI/ML methods for structure–property–processing predictions
- Creating data infrastructures (databases, ontologies, FAIR principles)
- Promoting open science and reproducibility through standardized workflows
- Hosting seminars, hands-on trainings, and interdisciplinary collaborations
The MDS Platform Cores
Research Data Management
Central data management with openBIS – electronic lab notebook, sample tracking, and FAIR-compliant workflows.
Databases
Sample databases with unique IDs and standardized metadata.
Machine Learning
AI/ML for structure–property predictions.
Seminars
Regular talks and interdisciplinary exchange on material data science.
Tutorials
Hands-on training for tools and methods.
MDS Steering Committee
