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https://github.com/camsai/standards
CAMSAI Standards provides schemas, validation tools, and data models for materials science and AI research. It ensures data consistency, interoperability, and quality across workflows. Built with Pydantic, it streamlines data integration and supports reproducible, collaborative research in the CAMSAI ecosystem.
https://github.com/camsai/standards
artificial-intelligence chemistry data-science json-schema machine-learning materials materials-design materials-informatics materials-science schemas
Last synced: about 6 hours ago
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CAMSAI Standards provides schemas, validation tools, and data models for materials science and AI research. It ensures data consistency, interoperability, and quality across workflows. Built with Pydantic, it streamlines data integration and supports reproducible, collaborative research in the CAMSAI ecosystem.
- Host: GitHub
- URL: https://github.com/camsai/standards
- Owner: camsai
- License: apache-2.0
- Created: 2024-10-17T00:59:11.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-12-13T10:29:13.000Z (about 1 month ago)
- Last Synced: 2025-01-14T00:40:51.306Z (1 day ago)
- Topics: artificial-intelligence, chemistry, data-science, json-schema, machine-learning, materials, materials-design, materials-informatics, materials-science, schemas
- Language: Python
- Homepage: https://github.com/camsai/standards
- Size: 19.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# CAMSAI Standards
The **CAMSAI Standards** repository defines and maintains a set of consistent schemas, validation tools, and data standards for materials science data and AI-driven research workflows. These standards ensure the interoperability, reproducibility, and scalability of materials-related datasets and applications across the CAMSAI ecosystem.
---
## **Purpose**
This repository provides:
- **Data Models**: Pydantic-based schemas for defining and validating data structures.
- **Validation Utilities**: Tools to ensure data compliance with established standards.
- **Interoperability Support**: Standards that facilitate seamless collaboration between different systems, tools, and workflows.
---
## **Key Features**
1. **Schema Definitions**
- Comprehensive data models for common materials science objects.
- Designed for compatibility with CAMSAI workflows and third-party applications.
2. **Validation Tools**
- Python utilities to validate data against the defined standards.
- Example workflows for integrating validation into your projects.
3. **Interoperability**
- Supports data exchange and integration across various CAMSAI and external platforms.
---
## **Repository Structure**
- **`src/py/camsai/standards`**
Contains Python files defining the Pydantic schemas for various data models by source/provider (e.g., Mat3ra.com).
---
## **Installation**
### Using `pip`:
You can install the repository using `pip` (requires Python 3.8+):
```bash
pip install camsai-standards
```
or from GitHub:
```bash
pip install git+https://github.com/camsai/standards.git
```
### In JupyterLite:
Install the package in a Pyodide-based JupyterLite environment:
```python
await micropip.install("camsai-standards")
```
---
## **Usage**
### Example: Validating a Material Schema
```python
from camsai.standards.mat3ra import Mat3raMaterialSchema
from camsai.standards import is_valid
# Example material data
material_data = {...}
# Validate data
if is_valid(Mat3raMaterialSchema, material_data):
print("Valid material data")
else:
print("Invalid material data")
```
### Example: Using Predefined Examples
```python
from mat3ra.esse.data.examples import EXAMPLES
example_material = next((e for e in EXAMPLES if e["path"] == "material"), None)["data"]
print(example_material)
```
---
## **Contributing**
We welcome contributions! To contribute:
1. Fork the repository.
2. Create a branch for your changes:
```bash
git checkout -b feature/new-schema
```
3. Commit your changes and open a pull request.
Please ensure all contributions are consistent with existing standards and include tests where applicable.
---
## **License**
This repository is licensed under the **Apache License 2.0**. See the [LICENSE](LICENSE) file for details.
---
## **Contact**
For questions or feedback, contact us at:
- **Email**: [[email protected]](mailto:[email protected])
- **Website**: [CAMSAI - Consortium for the Advancement of Materials Science with AI](https://camsai.org)