STREAM Project: Maturity Model for Experimental Materials Data based on FAIR Principles

Overview

This repository contains a module from the STREAM (Semantic Representation, networking and ‎Curating quality-assured material data‎) project by KIT (Karlsruhe Institute of Technology). It includes an Excel file aiming to create a maturity model for experimental materials data following the FAIR principles. This model assists in assessing the maturity level of data based on its Findability, Accessibility, Interoperability, and Reusability (FAIR).

File Structure

• MM_FAIRData.xlsx: Excel file containing the STREAM module for the maturity model.
• MMResults.py: Python script to extract data from the Excel file, plot the results, and generate a TTL file.
• README.md: This file providing an overview of the repository.

FAIR Principles

The maturity model aligns with the FAIR principles, emphasizing:

• Findability: Discoverability and location ease of the data.
• Accessibility: The ease of access to the data once discovered.
• Interoperability: The compatibility for different systems to work together and interpret the data.
• Reusability: The adaptability of data for various purposes.

Usage

Assessing Maturity Levels

1. Open Maturity_Model.xlsx using Microsoft Excel or a compatible spreadsheet application.
2. Follow the provided guidelines within the STREAM project to assess the experimental materials data based on the FAIR principles.
3. Input relevant data and information as required.
4. The model provides a structured approach to evaluate the maturity level of the data in each FAIR aspect.

Extracting Data and Generating TTL

• Run MMResults.py to extract data from the Excel file, plot the results, and generate a TTL file.

Contribution

Contributions to improve or expand this STREAM module are encouraged! To contribute:

• Fork the repository.
• Make your changes.
• Submit a pull request.

Acknowledgments

Special thanks to the STREAM project at KIT for providing this module.