These illustrations were contracted by the Heinrich Heine University of Düsseldorf in the frame of the consortium NFDI4BIOIMAGE from Henning Falk for the purpose of education and public outreach. The illustrations are free to use under a CC-BY 4.0 license.
NFDI4BIOIMAGE is a consortium of Germany's National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur, NFDI). NFDI4BIOIMAGE is a collaboration project comprising legally independent partners. The consortium is legally non-independent and does not act autonomously towards third parties
Please include an attribution similar to: "Data annotation matters", NFDI4BIOIMAGE Consortium (2024): NFDI4BIOIMAGE data management illustrations by Henning Falk, Zenodo, https://doi.org/10.5281/zenodo.14186100, is used under a CC BY 4.0 license. Modifications to this illustration include cropping.
NFDI4BIOIMAGE Consortium (2024): NFDI4BIOIMAGE data management illustrations by Henning Falk, Zenodo, https://doi.org/10.5281/zenodo.14186100, is used under a CC BY 4.0 license (accessed 9.29.24).
- Data annotation matters
- Discovering that your microscopic specimens produce macroscopic data
- Data steward
- Imaging data life cycle
- Data is available upon request
Bioimaging data provides unique insights into living and non-living matter with high spatial and temporal resolution, but the complexity of these experiments can present challenges. Metadata annotation is therefore essential for detailing the methods used in a bioimaging experiment and the way data was generated. This helps ensure your data is reusable and trustworthy. Help make your data findable, accessible, interoperable, and reusable (FAIR). Annotate your data with rich, descriptive metadata that comply with community standards, and share it in open file formats through public repositories –benefiting both your future self and the scientific community.
Microscopy modalities often generate large, complex image files stored in proprietary formats, making them difficult to manage and share. To effectively use these files throughout research, suitable storage solutions are needed, allowing frequent data access. Sharing and reusing this data require the ability to load large bioimaging files from remote sites over the Internet without downloading the entire file. NFDI4BIOIMAGE fosters developing OME-Zarr, a next-generation file format designed to become a standard for cloud-ready, large high-dimensional imaging data.
Overwhelmed by managing your research data? Handling, organizing, curating, annotating, and sharing scientific data can be quite challenging, especially in bioimaging. At NFDI4BIOIMAGE’s Help Desk, you’ll find enthusiastic scientists with a special expertise in managing complex bioimaging data. Don’t hesitate to reach out for tips, guidance, support, or even just a friendly chat about our shared passion: achieving excellent data for excellent science. Make your data findable, accessible, interoperable, and reusable (FAIR) to maximize its potential as part of your publication. The NFDI4BIOIMAGE Data Stewards are here to help.
Professionalizing your research data management practices not only makes your data reusable after publication, but also benefits you throughout your research journey. Begin by planning your research process ahead to pave yourself a smooth path along the bioimaging data life cycle. Writing a data management plan (DMP) upfront and using it as an adaptable guidance along the way will make your science more effective and efficient - for your future self and for science at large by sharing your data in a public repository. Reach out to the NFDI4BIOIMAGE Data Stewardship team for support on bioimage data management.
Providing the original data behind a scientific publication can be challenging, particularly when dealing with large, complex datasets. Simply stating that data would be available upon request is not enough and often does not hold true. Data should be findable, accessible, interoperable, and reusable (FAIR). This ensures that professional data scientists will be able to retrieve and reuse data for further analysis, develop novel processing and analysis tools, and assess data quality and reliability.Publish your data in a bioimaging-specific data repository using open file formats with rich metadata.
