EM and XRM Connectomics Imaging and Experimental Metadata Standards.

Area of Science:

• Neuroscience
• Bioinformatics
• Data Science

Background:

• High-resolution volumetric neuroimaging datasets from electron microscopy (EM) and X-ray micro/holographic-nano tomography (XRM/XHN) are rapidly increasing.
• These large-scale datasets, crucial for connectomics and understanding neural circuitry, lack standardized metadata, hindering integration and comparison.
• Existing neuroinformatics data standards do not yet cover EM and XRM/XHN connectomics data.

Purpose of the Study:

• To develop and introduce Image and Experimental Metadata Standards for EM and XRM/XHN data.
• To ensure the scientific impact and encourage the generation and sharing of these large-scale neuroimaging datasets.
• To support metadata services and future software designs for community collaboration in connectomics.

Main Methods:

• Formation of a working group with community stakeholders.
• Development of version 1.1 of Image and Experimental Metadata Standards for EM and XRM/XHN data.
• Documentation of standards for derived annotations in a companion document and availability on a community GitHub page.

Main Results:

• Establishment of version 1.1 of Image and Experimental Metadata Standards for EM and XRM/XHN connectomics data.
• The standards are designed to support metadata services and future software development.
• Standards definitions are publicly available on a community GitHub page.

Conclusions:

• The newly developed standards are expected to enable comparative connectomics analysis.
• These standards aim to improve interoperability between different connectomics software tools.
• The neuroinformatics community is encouraged to refine and improve these standards for future use.