Back to: Image Data Repositories

What makes a good repository for imaging data?

Public data sharing creates trust in scientific rigor, facilitates reproducibility and enables the potential reuse of data in other projects. Funding agencies may demand that original source data of a publication be published, too. Many journals either demand or at least strongly recommend publishing original source data. However, there are things to consider. For example, Nature Cell Biology‘s Submission Guidelines contain for bioimaging: „For imaging source data, we encourage deposition to a relevant repository due to size constraints.“ (last access: 2023-06-01)

So the question is: Where should one publish the data? And how does it get there?

Specifically for bioimaging data, there are two european general purpose repositories that were established in recent years:

• The BioImage Archive (BIA) – an archival-type repository (see also: featured post about the BioImage Archive)
• The Image Data Resource (IDR) – an added-value database (see also: featured post about the Image Data Resource)

Many domain-specific repositories exist, too, that may be suitable for your data.

General criteria for trustworthy repositories

Given that repository-deposited data is public to be found and reused by others, there are general criteria that one can orient along when choosing a repository. For example, the „Science Europe Guide Practical Guide to the International Alignment of Research Data Management“ (2021, Zenodo) outlines the following minimum criteria for trustworthy repositories:

1. Provision of Persistent and Unique Identifiers (PID)
   • Allow data discovery and identification
   • Enable searching, citing, and retrieval of data
   • Provide support for data versioning
2. Metadata
   • Enable finding of data
   • Enable referencing to related relevant information, such as other data and publications
   • Provide information that is publicly available and maintained, even for non-published, protected, retracted, or deleted data
   • Use metadata standards that are broadly accepted (by the scientific community)
   • Ensure that metadata are machine-retrievable
3. Data Access and Usage Licences
   • Enable access to data under well-specified conditions
   • Ensure data authenticity and integrity
   • Enable retrieval of data
   • Provide information about licensing and permissions (in ideally machine-readable form)
   • Ensure confidentiality and respect rights of data subjects and creators
4. Preservation
   • Ensure persistence of metadata and data
   • Be transparent about mission, scope, preservation policies, and plans (including governance, financial sustainability, retention period, and continuity plan)

(taken from: Science Europe. (2021). Practical Guide to the International Alignment of Research Data Management – Extended Edition. https://doi.org/10.5281/zenodo.4915862, license: http://creativecommons.org/licenses/by/4.0/)

Help for researchers to choose a suitable repository

The Science Europe Practical Guide also includes a section targeted to researchers to help them decide for a repository. Moreover, members of the international bioimaging community have come to consensus recommendations for repositories in the field of bioimaging (Swedlow et al, 2021). In brief, these include that repositories should:

• Have clear metadata specifications for submission
• Should integrate into the bioimage data ecosystem as either data archives or as added value databases (see: Introduction to Image Data Repositories and Public Archives)
• Should have clear author identification and also data access regulations
• Should meet trustworthiness criteria as catalogued, e.g., by FAIRsharing.org, or other resources
• Should follow recoginized guidelines on how to integrate person-identifiable data

Online registries to identify suitable repositories

As a researcher, it can be difficult to decide which repository is suitable for data deposition. Several of the abovementioned criteria are difficult to check for individuals. While professional data stewards at your research institutions (if available) may be able to help, a good approach is also to use repository registries: