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Fair Research Data Management Decision Tree

Overview

This decision tree serves as a visual and structured guide to help researchers, data managers, and institutions make more informed decisions about managing research data in alignment with FAIR(Findable, Accessible, Interoperable, and Reusable) principles. The goal of this decision tree is to provide a step-by-step framework to ensure that data management practices are met in order to ensure the quality, accessibility, and long-term usability of research data.

Purpose

This decision tree is designed to: -Enable researchers to check if their data meets the FAIR data standards. -Provide guidance on making key decisions related to data storage, sharing, documentation, and licensing. -Encourage practices that improve collaboration, transparency, and reproducibility in research.

Local hosting

If you want to increase your privacy, you can host this tool locally. First you need to clone this repository to your local system.

git clone https://github.com/fairagro/metadata_decision_tree.git

Now switch into the repository.

cd ./metadata_decision_tree

In order to run the tool, you need to host a local sever. One possible way is to install Python and run the following command.

python -m http.server 8000

If you don't have Python installed, visit https://www.python.org/ and download and install the latest stable version for your system. If you set up Python correctly, you can now run the previous command to host a local server.

While hosting the repository on a local server, the tool can be accessed in any web browser by opening http://localhost:8000.

About

This interactive website uses a decision tree to serve as a visual and structured guide to help researchers, data managers, and institutions make more informed decisions about managing research data in alignment with FAIR(Findable, Accessible, Interoperable, and Reusable) principles.

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