Evidence map›Paper›PMID 42156787›Full record

ArticleScientific data2026

Managing, Analyzing and Sharing Research Data with Gen3 Data Commons.

Craig Barnes, Kyle Burton, Michael S Fitzsimons, Hara Prasad Juvvala, Brienna Larrick, Ao Liu, Clint Malson, Noah Metoki-Shlubsky, Christopher Meyer, Andrii Prokhorenkov and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

20 authors.

Craig BarnesCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Kyle BurtonCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Michael S FitzsimonsCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Hara Prasad JuvvalaCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Brienna LarrickCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Ao LiuCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Clint MalsonCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Noah Metoki-ShlubskyCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Christopher MeyerCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.ORCID http://orcid.org/0000-0002-6180-6169
Andrii ProkhorenkovCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Jawad QureshiCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Radhika ReddyCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Pauline RibeyreCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
L Philip SchummCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.ORCID http://orcid.org/0000-0002-3050-2429
Mingfei ShaoCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Trevar SimmonsCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Alexander VanTolCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Peter VassilatosCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Aarti VenkatCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA.
Robert L GrossmanCenter for Translational Data Science University of Chicago, Chicago, Illinois, USA. rgrossman1@uchicago.edu.ORCID http://orcid.org/0000-0003-3741-5739

Funding

MEDICAL IMAGING AND DATA RESOURCE CENTER (MIDRC) YEAR 375N92020D00021 · NIBIB · UNIVERSITY OF CHICAGO · PI GIGER, MARYELLEN · 2021 to 2025
$16.6M
National Science Foundation (NSF) 2346212NHLBI NIH HHS 75N92020D00021
6 · The paper itself

Abstract

Gen3 is an open-source data platform for building data commons. A data commons is a cloud-based data platform for managing, analyzing, and sharing data with a research community. Gen3 has been used to build over 30 data commons by different organizations around the world. To set up a Gen3 data commons, you first define a data model. Gen3 then autogenerates 1) a data portal for searching and exploring data in the commons; 2) a data portal for submitting data to the commons; and 3) FAIR APIs for accessing the data programmatically. Gen3 is built over a small number of standards-based software services, which are designed to support current and future Gen3 components so that Gen3 can interoperate with other data platforms and data ecosystems.

Identifiers

PMID42156787
PMCPMC13454189

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.