COLD: Constructing Ontology-based Linked Data

COLD is a Python package for generating and validating battery-related linked data. It provides tools for structuring battery metadata and test data into RDF/JSON-LD formats using an ontology-driven approach. cold ensures that generated data adheres to well-defined ontologies, making it easy to integrate with semantic web technologies and battery digital twin ecosystems.

Features

• Ontology-Driven Linked Data Generation: Creates structured RDF/JSON-LD descriptions using EMMO and domain-specific battery ontologies.
• Validation of Linked Data: Ensures data correctness by checking against predefined ontology schemas.
• Metadata Structuring: Transforms raw battery test data into standardized linked data formats.
• Seamless Integration: Designed to work with battery ontologies and digital twin ecosystems.

Usage

• Documentation on how to install and get started can be found here: https://digibatt.github.io/cold/

Roadmap

• Enhanced Ontology Support: Expanding compatibility with more battery domain ontologies.
• Improved Validation Features: More detailed error reporting and schema checking.
• Extended Metadata Handling: Support for additional battery test data types.

Contributing

Contributions are welcome! To contribute:

1. Fork the repository
2. Create a new branch (feature-branch)
3. Commit your changes
4. Push to your branch and create a pull request

Acknowledgements

This project has received support from European Union research and innovation programs, under grant agreement numbers:

• 101103997 - DigiBatt