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FAQ: Research Data Express (RDE) - Data Infrastructure for Materials Science
TL;DR
NIMS's Research Data Express gives researchers an edge by automating data processing to create AI-ready datasets, accelerating materials discovery and innovation.
RDE uses Dataset Templates to automatically interpret raw experimental data, restructure it into readable formats, and perform analyses while maintaining FAIR principles.
This system promotes collaborative research by reducing data-sharing barriers, ultimately accelerating sustainable materials development for a better future.
RDE has already processed over 3 million files using 1,900 templates, showing how automation can transform materials science research.
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Research Data Express (RDE) is a highly flexible data management system developed by NIMS researchers that automates the processing of materials research data. It solves the problem of materials research data existing in manufacturer-specific formats with inconsistent terminology, which makes aggregation, comparison, and reuse difficult and discourages data sharing.
RDE is important because it reduces the burden of routine data processing for researchers and enhances data findability, interoperability, reusability (following FAIR principles), and traceability. This is particularly crucial as the field increasingly relies on AI-driven materials discovery, which requires high-quality datasets.
Unlike similar systems that typically 'define' data formats, RDE's core innovation is the 'Dataset Template' that defines and directs how data from different types of experiments should be processed. This allows researchers to freely define data structures tailored to their instruments while enabling the system to perform massive data structuring and metadata extraction automatically.
RDE was developed by researchers at Japan's National Institute for Materials Science (NIMS), led by corresponding author Jun Fujima from NIMS's Materials Data Platform. Since its launch in January 2023, it has been widely adopted across Japan's materials research community and serves as data infrastructure for major national initiatives including the Materials Research DX Platform initiative.
RDE automatically interprets experimental data from raw files and manually inputted measurements, then restructures and stores this information in a format with enhanced readability. It performs advanced analyses and creates visualizations to provide immediate overviews, significantly reducing the time researchers spend on tedious tasks like format conversion and metadata assignment.
RDE offers maximum flexibility through its Dataset Template system, where multiple templates can be prepared for different materials research themes, and custom templates can be easily prepared by individual researchers if necessary. Many templates have already been prepared and shared among users for various experimental methods.
RDE has over 5,000 users, with more than 1,900 Dataset Templates for various experimental methods implemented, over 16,000 datasets created, and more than three million data files accumulated, demonstrating its scalability and widespread adoption in Japan's materials research community.
The NIMS team has released an open-source software toolkit called RDEToolKit to encourage use of the system within the research community. The system was published in Science and Technology of Advanced Materials: Methods, and researchers can contact Jun Fujima at FUJIMA.Jun@nims.go.jp for further information.
Curated from NewMediaWire
