Insights into FAIR and Analyzable Data
Quality-controlled biomedical data, analyzed by AI/ML, holds the key to unlocking new treatments and cures.
It starts with the data.
FAIRLYZ Blog: Data Sharing in the Era of AI
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Federated Data Platforms vs. Data Visiting Technologies
What technologies and methods enable the access and analysis of sensitive data using AI/ML, while preserving data privacy and avoiding centralization? That’s the challenge federated data and data visitation technologies aim to solve. But are they the same thing? Not…
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Part 1: Key Takeaways from the RDA Plenary on AI/ML and Interoperability
The 23rd RDA Plenary Meeting in San José, Costa Rica, brought together a global community of researchers to address the pressing issue of sustainable science. The plenary was divided into many sessions that ran simultaneously and were organized by RDA…
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The FAIRLYZ Survey Report: Optimizing Data Sharing for Scientific Progress
Biomedical data sharing, especially crucial for AI’s reliance on large, high-quality datasets, fuels scientific progress by enabling new research and collaborations around data reuse, and the development of new tools trained on the data. To gain insights into current data…
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The Practice of Licensing Biomedical data
There are several reasons why a researcher might choose to license their data using permissive licenses like MIT, Apache 2.0, or LGPL including increased accessibility and collaboration. Benefits Benefits for the scientific community: Benefits for the Researcher: Alignment with Funding…
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Our comprehensive data sharing registry caters to a diverse group of researchers, ranging from investigators doing laboratory experiments to physician researchers and CROs running clinical trials.
FAIRLYZ Registry & Data QC
- Collaborate with fellow researchers
- Showcase your quality-controlled studies and data.
- Get funding for studies that reuse your data
- Run quality-control on your data or collaborators’ data

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