Learn about Research Data Life Cycle Implementation in DECIDE
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The Research Data Life Cycle
The research data life cycle illustrates the flow of data through a research project, highlighting key steps to ensure successful data curation and preservation. It consists of:
- Plan: Designing a data management plan (DMP) and outlining data collection and sharing protocols.
- Collect: Gathering primary or secondary data with clear metadata and data validation.
- Process and Analyze: Documenting workflows, software, and analysis steps to ensure transparency.
- Preserve: Storing data in standardized formats and preparing preservation documentation.
- Share: Publishing data securely while addressing copyright and access controls.
- Reuse: Leveraging data for follow-up research, education, and further analysis.
The life cycle emphasizes the importance of each step in preventing data loss and ensuring the reusability of results. Information provided by NFDI microbiota knowledgebase
DECIDE-Specific Tools and Resources in Data Life Cycle
Plan
Collect
- ELNs provided by Uni Würzburg
- User Meetings, Trainings, Focus Groups on ELNs, Nextcloud, Jupyterhub, Metadatacollection, Data Generation, Analysis
Process
Analyze
- HPC Julia I/II and HPC Bioinformatics including Jupyterhub
- Bioinformatics Tools
- Workflows
Preserve
- Nextcloud
- Long-term storage and archiving on Archive Server
Reuse
- Coming soon: Infection Atlas and Infection related network anaylsis