NIMS Researchers Develop Research Data Express to Automate Materials Science Data Processing

Materials research generates vast amounts of data, but the information often exists in manufacturer-specific formats with inconsistent terminology, making it difficult to aggregate, compare, and reuse. Traditionally, researchers have spent considerable time on tedious tasks like format conversion, metadata assignment, and characteristics extraction, which can discourage data sharing and hinder advancement in data-driven work. This problem is particularly acute given the field's increasing reliance on AI-driven materials discovery, which requires high-quality datasets.

To address this challenge, researchers at the National Institute for Materials Science (NIMS) have developed Research Data Express (RDE), a highly flexible data management system for materials scientists. Published in Science and Technology of Advanced Materials: Methods, RDE automatically interprets experimental data from raw files and manually inputted measurements, then restructures and stores this information in a format with enhanced readability. Jun Fujima, corresponding author and researcher at NIMS's Materials Data Platform, explains that RDE significantly reduces the burden of routine data processing for researchers and enhances data findability, interoperability, reusability (the FAIR principles), and traceability.

The system's core innovation is the Dataset Template, which defines and directs how data from different types of experiments should be processed. Unlike similar systems that define data formats, RDE's approach allows researchers to freely define data structures tailored to their instruments while enabling the system to perform massive data structuring and metadata extraction automatically. For example, if a researcher uploads spreadsheets of X-ray measurements from different sources, the Dataset Template can be configured to interpret them, with the system then automatically performing advanced analyses and creating visualizations to provide immediate overviews.

Multiple templates can be prepared for different materials research themes, allowing for maximum flexibility in data management, and custom templates can be easily prepared by individual researchers when necessary. Many templates have already been prepared and shared among users. Since its launch in January 2023, RDE has been widely adopted across Japan's materials research community, demonstrating its scalability with over 5,000 users, more than 1,900 Dataset Templates for various experimental methods implemented, over 16,000 datasets created, and more than three million data files accumulated.

The system serves as a data infrastructure for major national initiatives, including the Materials Research DX Platform initiative promoted by Japan's Ministry of Education, Culture, Sports, Science and Technology. The NIMS team has released an open-source software toolkit (RDEToolKit) to encourage use of the system within the research community. The research paper detailing this development is available at https://doi.org/10.1080/27660400.2025.2597702.