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Workshop Recap "Research Data Management in DFG Applications" (#9)

We are pleased to share the key takeaways from our latest workshop, where we explored the integration of Research Data Management (RDM) into DFG project proposals. This session offered valuable insights and practical guidance, addressing common questions to help consortium members better navigate this critical aspect of their applications.

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Why RDM Matters in DFG Applications

As RDM becomes an increasingly essential part of DFG proposals, it’s crucial for all consortium members to understand its role and requirements. To help prepare for this, we invited two experts, Daniela Hausen from the University Library and Urnaa Ritman from Division 4.2, to walk us through the DFG RDM Checklist. They provided a comprehensive overview of what to include in proposals, common challenges, and best practices.

Workshop Highlights

The workshop covered several important aspects, including:

  • DFG Proposal Overview: We began with an introduction to the structure of DFG, its funding sources, principles, opportunities for researchers, and the proposal review and decision-making process.

  • RDM in DFG Proposals: The focus then shifted to expectations regarding RDM in project proposals. The primary goal of RDM is to present your project and research in the best possible way, especially in relation to how research data will be managed throughout the project.

Key Viewpoints on RDM in DFG Proposals

Three core perspectives were emphasized when considering RDM:

  • Data Management as the Foundation of Research Activities:

            RDM is essential for organizing projects and ensuring efficient data handling.

            It also serves as a key enabler for enhanced knowledge generation.

  • Research Integrity:

            Emphasizing the transparency and reliability of your research process is crucial.

            Ensuring reproducibility is a key expectation.

  • Additional Impact:

            Beyond scientific articles, the importance of software and data publications is growing.

            DFG’s recent reforms include updated templates for CVs and a greater focus on evaluating scientific output.

            There is a general expectation for openness in research outputs.

Interactive Session: Tackling the DFG RDM Checklist

The most engaging part of the workshop was the deep dive into the DFG Checklist. Participants worked in small groups, using real examples to better understand the challenges and expectations.

We examined a real-life proposal that had been returned with a request for revision from the project office. The participants discussed in groups why the proposal was sent back and offered potential solutions. The primary issue identified was the lack of concrete details about how the research data would be managed. There was no clear plan for publishing or reusing the data, and access rights weren’t established, nor was it clear how to access the data. Additionally, technical data aspects were missing, such as how the data is structured, what software is used, and what type of data is generated.

 

 

 

 

 

Using a Miro board, participants brainstormed responses to the checklist questions, collaborating in small groups to improve their understanding. We then reviewed each point in detail to ensure everyone had a clearer understanding of what makes a strong RDM section in a DFG proposal.

Key Points from the DFG RDM Checklist

The DFG checklist contains six points:

  1. Data Description

  2. Documentation and Data Quality

  3. Storage and Technical Archiving

  4. Legal Obligations and Conditions

  5. Data Exchange and Long-Term Data Accessibility

  6. Responsibilities and Resources

Here are the most important infos for each section that you should provide:

  • Data Description:

    • Detailed descriptions of the types of data you have.

    • Organization of data.

    • Usage of Electronic Lab Notebooks (ELNs).

    • Volume of data for each type.

    • Specify the software involved.

    • New data or reused data.

  • Documentation and Data Quality:

    • Create Standard Operating Procedures (SOPs) for the consortium for standartisation

    • Use ELNs for traceable experiments and ensure sustainable data formats.

    • Include positive and negative controls.

    • Where possible: automate processes using scripts.

    • Employ domain-specific metadata schemas.

  • Storage and Technical Archiving:

    • Always store data on secure servers (e.g., Coscine).

    • Data should be encrypted, anonymized, or pseudonymized when necessary.

    • Backups are essential.

  • Legal Obligations and Conditions:

    • Data must be stored for at least 10 years.

    • Patient data should be anonymized.

  • Data Exchange and Long-Term Data Accessibility:

    • Archive data in repositories like Coscine or discipline-specific repositories for public data.

    • Consider licensing your data for reuse.

    • Think about what parts of your data could be suitable for reuse in other contexts.

    • Consider retention periode.

  • Responsibilities and Resources:

    • Typically, Principal Investigators (PIs) are responsible for adequate data handling since they have long-term involvement in the project.

    • Typically, Principal Investigators (PIs) are responsible for the curation of data after the end of the project.

    • While data stewards support the entire consortium, every individual is responsible for their own produced data:

      •     includes ensuring sustainable formats,

      • proper metadata,

      • adherence to SOPs, so the data is easily interpretable by others.

 

 

 

 

 

Conclusion

That wraps up our workshop on integrating RDM into DFG proposals. You can find more information about it in Moodle room. If you have any further questions or concerns, feel free to reach out to your data steward, and I’ll be happy to assist!

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Disclaimer

I hope this was an interesting read. If you have comments, remarks, or suggestions about other RDM-related topics for the next newsletters, please let me know by sending me an email at dukkart@itc.rwth-aachen.de.

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