Research data express: a data accumulation and sharing system for digital transformation in materials research

To accelerate the digital transformation (DX) in materials science, foundational technology for effectively managing vast amounts of data from diverse experiments and calculations and sharing them in a reusable format is essential. However, a significant barrier is that data formats, description styles, and terminologies differ among research fields, instrument manufacturers, and models, and are often not publicly available as readily usable schemas, making them unreadable. Research Data Express (RDE), introduced in this paper, is a highly flexible and scalable data accumulation and sharing system developed to solve these challenges. The core feature of RDE is the ‘Dataset Template’, which defines the format for data description and translation. Users can flexibly define data structures tailored to their research content using these templates. During data registration, raw files from experimental instruments and manually entered experimental conditions are automatically interpreted, integrated, and structured by a processing program defined in the template. This automated process includes metadata extraction, translation into common domain-specific terms, data visualization, and even the calculation of feature values for machine learning applications. In this paper, we detail the basic design and system architecture of RDE and explain the data management methodology based on Dataset Templates. RDE significantly reduces the burden of routine data processing for researchers and enhances data findability, interoperability, reusability (the FAIR principles), and traceability, thereby strongly promoting data-driven materials research.