BattINFO Converter: An Automated Tool for Semantic Annotation of Battery Cell Metadata

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Abstract
Driven by the global demand for batteries with improved performance, cost efficiency, and sustainability, battery research has expanded rapidly during recent years, generating a surge in data which offers the potential to accelerate the discovery of new battery materials, optimize battery cell manufacturing processes, and enable predictive modeling of battery aging. However, the lack of adoption of a community‐wide battery data reporting standard results in significant challenges in integrating battery research data across different studies, limiting the potential for automated analysis and large‐scale comparative studies. To foster the widespread adoption of a standardized battery data reporting framework, BattINFO converter, an open‐source, Python‐based web application is developed that facilitates the conversion of battery cell data and metadata from an Excel table into a structured, semantically annotated, linked data format compliant with the BattINFO ontology. The BattINFO ontology defines clear relationships between data and metadata items, thereby enhancing machine readability, interoperability, and discoverability. By facilitating the adoption of a standardized approach to data annotation, BattINFO converter supports more efficient data sharing, analysis, and integration within the battery research community.

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