NBO-Q
Harmonize the description of light microscopy hardware, acquisition settings, and quality-control metrics in order to enhance image quality, reproducibility, and to fulfill the FAIR (Findable, Accessible, Interoperable, and Reusable) data principles.
Purpose
- Promote the harmonized generation and pre-publication management of image datasets from the ground up.
- Facilitate the deposition of microscopy datasets to public image data repositories (e.g., BioImage Archive, OME-Image Data Resource, RIKEN SSBD, Brain Image Library, etc.).
- Facilitate data reuse and the extraction of quantitative information from image data using advanced bioimage analysis techniques, including AI/ML.
- Define the light-microscopy implementation of the Image Acquisition module of the Recommended Metadata for Biological Images (REMBI) guidelines.
Deliverables
- A flexible and adaptable community-agreed vocabulary to describe microscopy hardware, image acquisition settings, and their associated quality control measurements.
- A metadata model to structure the vocabulary and organize the data.
- A set of machine-actionable representations of the metadata model leveraging the latest Linked Data technology.
Getting started
Imaging Scientists
- Read about the model on Nature Methods
- Leverage the model to annotate your images with the Micro-Meta App
Developers
- Familiarize yourself with the structure of the model on GitHub
- Learn about how you can use the specifications for your application by following the Micro-Meta App example
NBO-Q Specifications
How to join and access
Specifications
Become a member of QUAREP-LiMi WG7 (Metadata)
Open an issue on GitHub to ask a question or propose a change
Become a contributor to the GitHub repository
Governance
Summary of current processes and link to Best-Practices document or page describing the process in detail
Learn more about how NBO-Q was developed to update the Open Microscopy Environment (OME) Data Model.