FAIRy is a local-first dataset validator and submission readiness tool. It helps researchers and institutions check their data before it's handed off — to a repository, a core facility, a collections manager, whoever's on the receiving end.
FAIRy runs entirely on your computer. Nothing is uploaded. It looks at your files and metadata, checks them against a defined set of rules, and tells you exactly what needs to be fixed before someone rejects the dataset.
Datadabra is the company building FAIRy.
We're doing that in two layers:
FAIRy Core (open)
The core validator — the part that runs locally, flags missing/invalid fields, checks naming/ID consistency, and generates a one-page readiness report — is being built to stay available to researchers and labs. The goal is that you can run it yourself, get a clear "fix these items" list, and avoid getting bounced. This tool will be freely available to support the FAIR data sharing standards and our vision.
FAIRy for Institutions
Institutions have a different problem: they need repeatable intake. We work with data stewards, curators, and core facilities to encode "this is what we require before we accept your data" into a rulepack. FAIRy then produces two things they can actually use:
- a Submission Readiness Report they can send back to the submitter, and
- an Attestation file — a timestamped record of what was checked, under which rules, and on which files by hash — that can be kept internally for review, audit, or compliance.
The mission behind both is the same: make research data usable, not just technically "published," and stop wasting expert time on preventable back-and-forth.