8 Standards

There are many field and community-specific standards describing how to structure data and metadata, filenaming conventions and file formats. We recommend searching for what is available, reusing it or modifying it just as much as necessary. Adopting available community standards will result in a much lower workload than defining a new standard from scratch. We recommend adopting standards that are actively maintained, well documented and that are used by a broad community for some time. If no standard is available for a specific data type or community, it is preferable to adapt standards for similar data types than to create a new one. Some popular standards offer the possibility of submitting extension proposals for additional data types.

8.1 Finding data structure standards

Data stewards or researchers involved in planning data management may need to conduct a systematic search for field-specific metadata standards.

The FAIRsharing (https://fairsharing.org/) resource is an extensive list of data and metadata standards, databases, and policies, and it is kept up-to-date by the field-specific research communities (Sansone et al. 2019).
The Digital Curation center of the UK also offers a list of metadata standards organized by discipline: https://www.dcc.ac.uk/guidance/standards/metadata

8.2 Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) (Gorgolewski et al. 2016) describes a series of data organization principles to facilitate large-scale data sharing between researchers, while also making metadata machine-readable to allow automation. It started in 2015 and it can be considered one of the most complete guidelines in neuroimaging. It covers a range of imaging modalities (MRI, EEG, iEEG, MEG, PET, CT, microscopy). Although initially focused on human data it has ongoing extension developments related to animal research data. Since 2020, the BEP032 project has been developing a proposal for animal electrophysiology and associated tools. The BIDS extension proposals (BEP) process allows researchers to propose BIDS specifications for their data modality, which are then reviewed and integrated into the standards. BIDS guidelines cover multiple aspects of data management including:

Data structure
Metadata
File names and formats
Preprocessing and analysis workflows

The defining features of BIDS are those desirable in most standards:

Flexible and easy-to-adopt. BIDS combines technically complex documentation with more accessible guides and apps to facilitate adherence, particularly for early-career researchers. The BIDS Starter Kit collects tutorials, wikis, and templates to help any lab get started with BIDS.
Community-driven, platform-independent, and growing. BIDS was developed by researchers and it has evolved from its initial focus on human functional magnetic resonance imaging to accommodate other data modalities (EEG, MEG, PET, CT, microscopy).
An ecosystem of resources. BIDS has fostered an ecosystem of tools and resources, including validation tools, apps for data preprocessing, and databases like OpenNeuro.

8.3 The Open Microscopy Environment (OME) and related standards

The Open Microscopy Environment (OME; https://www.openmicroscopy.org/) is a consortium of universities, research labs, industry and developers producing open-source software and format standards for microscopy data. It was stablished in 2005 and remains very active. OME has its own collection of standards listed in the FAIRsharing platform: https://fairsharing.org/OME.

The different microscopy techniques and image modalities have led to multiple initiatives to create specific standards built on or extend the OME data model (Goldberg et al. 2005). Some of these community-extensions are discussed in Ropelewski et al. (2022) and (Sarkans et al. 2021). There is also an active BIDS extension for microscopy data (Bourget et al. 2022).

Bourget, Marie-Hélène, Lee Kamentsky, Satrajit S. Ghosh, Giacomo Mazzamuto, Alberto Lazari, Christopher J. Markiewicz, Robert Oostenveld, et al. 2022. “Microscopy-BIDS: An Extension to the Brain Imaging Data Structure for Microscopy Data.” Frontiers in Neuroscience 16. https://doi.org/10.1038/s41598-018-22181-4.

Goldberg, Ilya G, Chris Allan, Jean-Marie Burel, Doug Creager, Andrea Falconi, Harry Hochheiser, Josiah Johnston, Jeff Mellen, Peter K Sorger, and Jason R Swedlow. 2005. “The Open Microscopy Environment (OME) Data Model and XML File: Open Tools for Informatics and Quantitative Analysis in Biological Imaging.” Genome Biology 6 (5): R47. https://doi.org/10.1186/gb-2005-6-5-r47.

Gorgolewski, Krzysztof J., Tibor Auer, Vince D. Calhoun, R. Cameron Craddock, Samir Das, Eugene P. Duff, Guillaume Flandin, et al. 2016. “The Brain Imaging Data Structure, a Format for Organizing and Describing Outputs of Neuroimaging Experiments.” Scientific Data 3 (1): 160044. https://doi.org/10.1038/sdata.2016.44.

Hammer, Mathias, Maximiliaan Huisman, Alessandro Rigano, Ulrike Boehm, James J. Chambers, Nathalie Gaudreault, Alison J. North, et al. 2021. “Towards Community-Driven Metadata Standards for Light Microscopy: Tiered Specifications Extending the OME Model.” Nature Methods 18 (12): 1427–40. https://doi.org/10.1038/s41592-021-01327-9.

Ropelewski, Alexander J., Megan A. Rizzo, Jason R. Swedlow, Jan Huisken, Pavel Osten, Neda Khanjani, Kurt Weiss, et al. 2022. “Standard Metadata for 3D Microscopy.” Scientific Data 9 (1): 449. https://doi.org/10.1038/s41597-022-01562-5.

Sansone, Susanna Assunta, Peter McQuilton, Philippe Rocca-Serra, Alejandra Gonzalez Beltran, Massimiliano Izzo, Allyson L. Lister, and Milo Thurston. 2019. “FAIRsharing as a Community Approach to Standards, Repositories and Policies.” Nature Biotechnology 37 (4): 358–67. https://doi.org/10.1038/s41587-019-0080-8.

Sarkans, Ugis, Wah Chiu, Lucy Collinson, Michele C. Darrow, Jan Ellenberg, David Grunwald, Jean-Karim Hériché, et al. 2021. “REMBI: Recommended Metadata for Biological Imagesenabling Reuse of Microscopy Data in Biology.” Nature Methods 18 (12): 1418–22. https://doi.org/10.1038/s41592-021-01166-8.