Welcome to ct.qmat Research Data Management

This portal provides comprehensive information and guidelines on Research Data Management (RDM) within the ct.qmat Cluster of Excellence. Our goal is to support researchers in managing their data efficiently, ensuring reproducibility, and adhering to the FAIR principles (Findable, Accessible, Interoperable, Reusable).

Here you will find information on our policies, the infrastructure we provide, and practical guides for publishing data and software.

Overview

Data Management Policies and Publication Guidelines

Learn about the principles that guide our data management strategies, including the FAIR and FAIR4RS principles. This section outlines why efficient data management is crucial for the scientific community and the cluster.

ct.qmat Research Data Infrastructure

Explore the tools and services available to ct.qmat members. This includes our central user login system, the electronic lag notebook eLabFTW, the NOMAD Oasis for materials science data, and other collaborative tools like GitLab and JupyterHub.

Guide: How to publish your research data

A practical guide on choosing the right repository for your research data. We recommend using NOMAD for materials science data, but also provide alternatives for other types of data.

Guide: How to move your software to a distributed development platform

If you are developing software, this guide helps you migrate to distributed version control systems like GitHub or GitLab. It offers advice for both new and existing projects, including templates to get you started.