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Published on: July 7, 2014
Enabling global image data sharing in the life sciences
Peter Bajcsy1, Sreenivas Bhattiprolu2, Katy Börner3
1National Institute of Standards and Technology, Gaithersburg, MD, USA.
Nature Methods
|March 29, 2025
Summary
Making biological and medical image data FAIR (findable, accessible, interoperable, and reusable) is crucial. Public funders must invest in open data resources to support scientists and unlock the value of imaging research.
Area of Science:
- Biological imaging
- Medical research
- Data science
Background:
- Vast amounts of valuable biological and medical image data remain inaccessible.
- Lack of data accessibility hinders scientific rigor and reuse.
- Image data FAIRification is essential for scientific discovery.
Purpose of the Study:
- To advocate for public funders' support in making image data FAIR.
- To highlight the need for openly accessible, long-term image data storage resources.
- To emphasize the importance of national investment in open data infrastructure.
Main Methods:
- Global collaboration among image data experts.
- Development of common data formats, metadata, and ontologies.
- Focus on FAIRification tools and strategies.
Main Results:
- Existing international collaborations (Australia, Japan, Europe) are working towards global image data sharing.
- Urgent need for openly accessible, long-term operated data storage resources.
- Current efforts will be insufficient without increased national investment.
Conclusions:
- Public funders must invest in national open data resources for image data.
- Federated open data resources are vital for global image data sharing.
- Investment in FAIR image data infrastructure maximizes the value of imaging research.
