Evidence map›Paper›PMID 35651719›Full record

ArticleFrontiers in neuroinformatics2022

Connectomics Annotation Metadata Standardization for Increased Accessibility and Queryability.

Morgan Sanchez, Dymon Moore, Erik C Johnson, Brock Wester, Jeff W Lichtman, William Gray-Roncal

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in neuroinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Morgan SanchezResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
Dymon MooreResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
Erik C JohnsonResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
Brock WesterResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
Jeff W LichtmanDepartment of Molecular and Cellular Biology, Harvard University, Cambridge, MA, United States.
William Gray-RoncalResearch and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.

Funding

Boss: A cloud-based data archive for electron microscopy and x-ray microtomographyR24MH114785 · NIMH · JOHNS HOPKINS UNIVERSITY · PI BROCK A. WESTER · 2018 to 2026
$6.9M
Big-Data Electron-microscopy for Novel Community Hypotheses: Measuring And Retrieving Knowledge (BENCHMARK)R01MH126684 · NIMH · JOHNS HOPKINS UNIVERSITY · PI GRAY RONCAL, WILLIAM R · 2021 to 2022
$1.3M
SABER: Scalable Analytics for Brain Exploration Research using X-Ray Microtomography and Electron MicroscopyR24MH114799 · NIMH · JOHNS HOPKINS UNIVERSITY · PI GRAY RONCAL, WILLIAM R · 2017 to 2019
$1.2M
NIMH NIH HHS R01 MH126684NIMH NIH HHS R24 MH114785NIMH NIH HHS R24 MH114799
6 · The paper itself

Abstract

Neuroscientists can leverage technological advances to image neural tissue across a range of different scales, potentially forming the basis for the next generation of brain atlases and circuit reconstructions at submicron resolution, using Electron Microscopy and X-ray Microtomography modalities. However, there is variability in data collection, annotation, and storage approaches, which limits effective comparative and secondary analysis. There has been great progress in standardizing interfaces for large-scale spatial image data, but more work is needed to standardize annotations, especially metadata associated with neuroanatomical entities. Standardization will enable validation, sharing, and replication, greatly amplifying investment throughout the connectomics community. We share key design considerations and a usecase developed for metadata for a recent large-scale dataset.

Indexed as

annotationconnectomequeriesreproducibilitysoftwarestandard

Identifiers

PMID35651719
PMCPMC9150677

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.