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The role of Colibri is to collect the experiment correctly at the source.
That means preserving the relationship between image data, microscope metadata, holder conditions, environmental parameters, timestamps, sample context, user notes, and downstream export paths.
For an in-situ TEM experiment, that context may include:
Without this context, the data may still produce an image. But it loses much of its scientific value.
LIMS-ready TEM data means the experiment is no longer trapped in a folder of disconnected files.
It means the data is structured enough to search. Documented enough to trust.
Synchronized enough to compare. Portable enough to export. Open enough to connect. Complete enough to support future analysis, publication, automation, and AI workflows.
Colibri is designed as a platform for data movement, not software lock-in.
That platform direction has three parts.
First, Colibri supports structured export. Experimental data and metadata should be captured in documented, portable formats so customers can move the data into storage, analysis, publication, or archive workflows.
Second, Colibri supports API-based handoff. Laboratories, OEM environments, institutional repositories, open-source tools, and custom research pipelines should be able to connect to the data without depending on a closed desktop application.
Third, Colibri can support direct connectors where they make sense. Customers may want data delivered to selected LIMS platforms, ELNs, institutional repositories, cloud storage systems, local servers, OEM microscope environments, Python workflows, open-source microscopy tools, or future AI-ready pipelines.
The customer decides where the data goes.
The scientific community does not need every microscope accessory vendor to reinvent laboratory information management.
Highly developed commercial LIMS platforms already exist. Open-source systems already exist. National laboratories and standards organizations have already invested deeply in research-data infrastructure, metadata, FAIR data practices, materials data curation, and microscopy experiment records.
The better path is to build with that ecosystem, not against it.
Colibri is designed to support that direction by focusing on the acquisition and handoff layer:
Better data in.
Better metadata with it.
Better freedom after acquisition.
Hummingbird Scientific believes customers should own their experimental workflows.
That means a laboratory should be free to use the LIMS, ELN, repository, OEM software, open-source tool, cloud system, local server, or analysis environment that works best for its research.
Colibri helps make that possible by collecting synchronized, metadata-rich TEM data and delivering it where it needs to go.
Not software lock-in. Not another data island. Not a closed workflow pretending to be a laboratory platform.
LIMS-ready TEM data.
Customer-owned workflows.
Open handoff to the tools that matter.

https://pages.nist.gov/NexusLIMS/
Backend LIMS that automatically harvests microscopy data and builds structured XML experiment records.
https://github.com/usnistgov/NexusLIMS-CDCS
Front-end interface (based on CDCS) used to access, browse, and manage NexusLIMS XML experiment records.
https://www.nist.gov/programs-projects/materials-data-curation-system
XML-based platform for structured materials data curation, transformation, and sharing.
https://www.nist.gov/programs-projects/configurable-data-curation-system-cdcs
General-purpose, FAIR-oriented data curation platform supporting schemas, interoperability, APIs, and modular systems.
https://www.nist.gov/publications/nist-research-data-framework-rdaf-version-20
Customizable framework for building research data management strategies across the data lifecycle.
https://www.nist.gov/programs-projects/nist-materials-resource-registry
Registry for discovering materials data resources, with metadata, interoperability, and API/web-service concepts.
Community best-practice recommendations for FAIR microscopy data, metadata standards, and LIMS usage.
https://4ceed.github.io/
Open-source ecosystem for uploading, extracting, organizing, and curating scientific data and metadata.