What problem we solve
- Reproducibility crisis in biomedical research
- Experimental metadata lost to spreadsheets and silos
- Valuable data that can't be reused across studies or labs
- Animal experiments repeated because data wasn't structured to travel
Open Source
The FAIR metadata backbone for preclinical research
Structure your experiments. Reuse your data. Better science means fewer animals.
✦FAIR by design✦JSON-LD / RO-Crate✦Self-hostable AGPL-3.0
What Metadatapp is / is not
Not an ELN. Not a LIMS. Not an AMS.
Metadatapp sits above these systems as a shared metadata layer.
Metadatapp is:
- A FAIR-by-design metadata platform (AGPL-3.0)
- Symfony/API Platform backend + Osoma React frontend
- JSON-LD, RO-Crate, and ontology-based data modelling
- AI-ready research data workflows
Built for open science workflows
Useful for labs, data stewards, and communities that want reusable research metadata.
Research labs
Capture experimental context once, preserve provenance, and make datasets easier to reuse across cohorts and collaborators.
Data stewards & engineers
Use APIs, JSON-LD, RO-Crate, and self-hosted infrastructure to connect metadata with existing lab systems.
Open science communities
Build shared schemas, examples, and reusable workflows that help research data travel without losing meaning.
Why now
- Open science mandates (Horizon Europe, NIH data sharing) require FAIR outputs
- AI and ML pipelines are hungry for structured, comparable research data
- 3Rs: reusable, traceable data is the most direct path to animal use reduction
- FAIR principles now expected by journals, funders, and repositories
- Community-ready: open source (AGPL-3.0), self-hostable, extensible
FAIR by design
Metadatapp isn't merely "compatible" with FAIR — it makes FAIR measurable and automatic:
- Every capture follows controlled vocabularies and ontology-based schemas.
- JSON-LD and RO-Crate exports make data machine-readable and repository-ready.
- Provenance is preserved from study design to final dataset.
- AI/ML pipelines get clean, structured inputs — no preprocessing chaos.
Workflows made visible
01
Capture
Investigations → Studies → Assays. Ingest from LIMS/ELN/AMS with lineage intact.
02
Standardize
JSON-LD + RO-Crate + ontology validation so every subject and assay stays comparable across labs and time. See FAIR.
03
Reuse & Decide
Assets, not files: export, reanalyze, and compare across cohorts. Browse the use cases timeline.
ROI and reduction
Fewer repeats
Traceable metadata → higher statistical power → fewer repeated experiments.
Earlier go/no-go
Better monitoring → fewer missed phenotypes → earlier decisions.
Less waste
Cross-site reuse → reduced duplication and cleaner transfers.
Quantify it
Ask: “How many mice could we reduce with 30% reuse of traceable behavioral metadata?” Talk to us.
Q & A
Does Metadatapp replace my ELN or LIMS?
No. Metadatapp connects with your existing systems—ELNs, LIMS, HCM platforms—to avoid duplicate entry. It serves as a metadata hub that enriches, links, and harmonizes what you already capture.
What kind of data and standards does Metadatapp support?
Metadatapp manages experimental metadata — subjects, protocols, devices, and outcomes — using ontology-based standards: JSON-LD, RO-Crate, ARRIVE, and FAIR principles, with NWB support coming. Exports integrate with repositories, publications, and AI workflows. Learn more in <a href="/fair-by-design">FAIR-by-Design</a>.
How does better metadata reduce animal use?
Structured, FAIR metadata makes experiments reusable. When data travels across labs and time without losing context, researchers find existing evidence instead of repeating experiments. Fewer repeated studies means fewer animals — not as a reporting checkbox, but as a direct consequence of better data.
What export and integration options are available?
Export to JSON-LD, RO-Crate, CSV, and JSON. Integrate with analytics tools, repositories (OSF, Zenodo), ELNs (elabFTW), and animal management systems. NWB support coming.
Who is Metadatapp for?
Metadatapp is for research labs, data stewards, software engineers, and open science communities that need reusable experimental metadata.
The Team
Damien Huzard
Creator and maintainerBehavioral neuroscientist and creator of Metadatapp. Leads open-source development at Neuronautix with the help of an AI agent toolchain. Works at the intersection of behavior, physiology, and data science — building tools that make research data worth reusing. Co-developed LWTools; runs TheBehaviourForum.org.
ORCID
Laurent Huzard
Backend Expert & API Platform InitiatorBuilt the original Metadatapp backend — the Symfony/API Platform architecture you see today is, in large part, his work. Backend expert in API design, system architecture, and scalable module delivery.
Latest updates
View all →Jan 21, 2026
VICT3R Webinar: Standardization and Reuse of Data from Academic In Vivo Studies
Key takeaways from Damien Huzard's VICT3R webinar on FAIR metadata, operational standardization, and reuse in preclinical in vivo research.
Read more →
Nov 1, 2024
Welcome to Metadatapp
How we make preclinical metadata FAIR-by-design.
Read more →