README.md

Dataset for publication "Toward an Autonomous Robotic Battery Materials Research Platform Powered by Automated Workflow and Ontologized Findable, Accessible, Interoperable, and Reusable Data Management"

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🔬 Scope

• The dataset comprises detailed data from 199 coin cell batteries with either NMC//graphite or LFP//graphite chemistry. :contentReference[oaicite:14]{index=14}
• All battery cells were assembled and cycled using the automated robotic battery-materials research platform Aurora at Empa, the Swiss Federal Laboratories for Materials Science and Technology, within the Laboratory for Materials for Energy Conversion. :contentReference[oaicite:15]{index=15}
• Each battery was cycled for 1000 cycles under fully automated and precisely controlled conditions. :contentReference[oaicite:16]{index=16}
• The dataset supports the peer-reviewed publication: Toward an Autonomous Robotic Battery Materials Research Platform… (Batteries & Supercaps, 2025). :contentReference[oaicite:17]{index=17}

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📁 Data Structure

• The dataset is packaged as a RO-Crate (Research Object Crate) to facilitate standardized, machine-readable, and FAIR-compliant data sharing. :contentReference[oaicite:18]{index=18}

For each battery cell, the following files are included:

1. Battery Cell Metadata File

• Filename: empa__ccid000XXX.metadata.json :contentReference[oaicite:19]{index=19}
• Contents: Semantically annotated battery assembly data and the cycling protocol applied to that battery cell.
• Format: JSON-LD, using the Battery Interface Ontology (BattINFO) to ensure semantic interoperability and rich metadata representation. :contentReference[oaicite:20]{index=20}

2. Battery Cell Cycling Data Files

• Filenames:
  • empa__ccid000XXX.bdf.csv
  • empa__ccid000XXX.bdf.parquet :contentReference[oaicite:21]{index=21}
• Description: Both files contain identical cycling data.
  • .csv — for easy human inspection.
  • .parquet — for faster automated parsing and processing.
• Format: Conform to the Battery Data Format (BDF) for time-series data, as recommended by the Battery Data Alliance. :contentReference[oaicite:22]{index=22}

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📦 Files Included in the Dataset

• Dataset-rocrate.zip — contains the full RO-Crate. :contentReference[oaicite:23]{index=23}
• The archive is approximately 2.5 GB in size. :contentReference[oaicite:24]{index=24}

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📌 Additional Details

• License: Creative Commons Attribution 4.0 International (CC-BY 4.0) — allows redistribution and reuse with appropriate credit. :contentReference[oaicite:25]{index=25}
• Related Publication: 10.1002/batt.202500155 (Batteries & Supercaps, 2025) — describes the robotic platform, workflow, and data management strategy. :contentReference[oaicite:26]{index=26}
• Purpose / Importance: Released by the Battery Data Alliance (BDA) in cooperation with Empa and partners to set a new standard for battery-research data: FAIR-compliant, traceable, interoperable and suitable for automated data analysis pipelines. :contentReference[oaicite:29]{index=29}

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🧪 Usage Notes

• You can download and unpack the RO-Crate to access metadata and cycling data for all 199 batteries. :contentReference[oaicite:30]{index=30}
• The JSON-LD metadata facilitates semantic queries (e.g., via ontology-aware tools) to filter batteries by chemistry, assembly protocol, cycling conditions, etc.
• The BDF cycling data — in .parquet — is well suited for automated analysis workflows (e.g., in Python or Julia), enabling time-series analysis, degradation modelling, machine learning, etc.

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