Research Data Management
Effective data management is fundamental to our research, ensuring that data is organized, accessible, and reusable. We adhere to the FAIR principles—Findable, Accessible, Interoperable, and Reusable—to maintain high standards in data handling, supporting transparency, reproducibility, and long-term impact.
Collaborations Enhancing Data Management
Our partnership with DataPLANT, part of the National Research Data Infrastructure (NFDI) initiative, has been instrumental in advancing data management within plant sciences. DataPLANT provides innovative tools and resources for annotating and managing research data, simplifying integration with existing IT infrastructures, and fostering collaboration across the scientific community. The Data Stewardship initiative in our group originated within the framework of DataPLANT, with Jens Krüger from the University of Tübingen’s Center for Data Processing (ZDV) playing a key role in its establishment. Jens’s expertise and contributions were pivotal in developing the foundational practices that now guide our data management strategies.
At the University of Tübingen, we also collaborate closely with QBiC (Quantitative Biology Center), which supports our research with advanced bioinformatics and omics services. QBiC provides robust data analysis pipelines, secure data storage, and expertise in handling high-throughput datasets, ensuring reliability and efficiency in our research workflows.
To complement these efforts, we have implemented electronic lab notebooks (eLabFTW) and lab management systems in collaboration with Jens Krüger and our data steward. These systems streamline documentation, enhance workflow transparency, and integrate seamlessly with our broader data management infrastructure, supporting efficient and reliable record-keeping in our experimental research.
Data Management Practices
Our data management strategy encompasses several key practices:
- Standardization: We employ standardized formats and protocols for data collection and storage, ensuring consistency and interoperability across all projects.
- Metadata Annotation: Comprehensive metadata is recorded for all datasets, providing detailed context and ensuring accurate interpretation and reuse.
- Data Sharing: We promote open data sharing within the scientific community, following ethical guidelines and ensuring compliance with privacy standards.
- Lab Documentation and Management: Through eLabFTW, we ensure that experimental workflows are well-documented, accessible, and fully integrated with our data management systems.
- Training and Support: We provide ongoing training in data management to team members, fostering a culture of excellence and best practices.
Supporting the Scientific Community
We are currently in the process of publishing several of our fully annotated datasets, ensuring that the data we have generated becomes a valuable resource for the broader scientific community. By providing high-quality, standardized datasets, we aim to enable other researchers to build upon our work, fostering collaboration and accelerating discoveries in plant-microbe interactions and microbial ecology. This approach takes full advantage of the data we have produced, maximizing its value beyond our own research.
Key to generating these datasets and supporting our data management efforts has been EU funding through the DeCoCt project. This funding has provided the resources necessary to produce high-quality data and establish robust data management practices, setting a benchmark for reproducibility and transparency in plant science research.