Evidence map›Paper›PMID 39952970›Full record

ArticleScientific data2025

Ensuring Adherence to Standards in Experiment-Related Metadata Entered Via Spreadsheets.

Martin J O'Connor, Josef Hardi, Marcos Martínez-Romero, Sowmya Somasundaram, Brendan Honick, Stephen A Fisher, Ajay Pillai, Mark A Musen

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. The HuBMAP Framework for Advancing Data FAIRness.bioRxiv : the preprint server for biology · 2026
    Article
  3. The FAIRSCAPE AI-readiness Framework for Biomedical Research.bioRxiv : the preprint server for biology · 2026
    Article
  4. Article
  5. 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

8 authors.

Martin J O'Connor *Stanford Center for Biomedical Informatics Research, Stanford, CA, 94305, USA. martin.oconnor@stanford.edu.ORCID http://orcid.org/0000-0002-2256-2421
Josef Hardi *Stanford Center for Biomedical Informatics Research, Stanford, CA, 94305, USA.
Marcos Martínez-RomeroStanford Center for Biomedical Informatics Research, Stanford, CA, 94305, USA.ORCID http://orcid.org/0000-0002-9814-3258
Sowmya SomasundaramStanford Center for Biomedical Informatics Research, Stanford, CA, 94305, USA.
Brendan HonickPittsburgh Supercomputer Center, Pittsburgh, PA, 15213, USA.
Stephen A FisherUniversity of Pennsylvania, Philadelphia, PA, 19104, USA.ORCID http://orcid.org/0000-0001-8034-7685
Ajay PillaiNational Human Genome Research Institute, Bethesda, MD, 208792, USA.ORCID http://orcid.org/0000-0002-9789-7189
Mark A MusenStanford Center for Biomedical Informatics Research, Stanford, CA, 94305, USA.ORCID http://orcid.org/0000-0003-3325-793X

Funding

SenNet Supplement - Consortium BenchmarkingU24CA268108 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Philip D. Blood, JONATHAN C. SILVERSTEIN · 2021 to 2026
$22.1M
Flexible Hybrid Cloud Infrastructure for Seamless Integration and Use of Human Biomolecular Data and Reference Maps [1 of 5]OT2OD033759 · OD · CARNEGIE-MELLON UNIVERSITY · PI BLOOD, PHILIP D., SILVERSTEIN, JONATHAN C. · 2022 to 2025
$20.4M
Penn TMC: Organ-Specific ProjectU54HD104392 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI KIM, JUNHYONG, O'NEILL, KATHLEEN ELISE · 2020 to 2024
$6.1M
BioPortal: An Expansive Knowledgebase of Biomedical Entities and RelationsU24GM143402 · NIGMS · STANFORD UNIVERSITY · PI MUSEN, MARK A · 2021 to 2024
$4.5M
The Metadata Powerwash - Integrated tools to make biomedical data FAIRR01LM013498 · NLM · STANFORD UNIVERSITY · PI MUSEN, MARK A · 2021 to 2024
$1.8M
NCI NIH HHS U24 CA268108NICHD NIH HHS U54 HD104392NIGMS NIH HHS U24 GM143402NIH HHS OT2 OD033759NLM NIH HHS R01 LM013498
6 · The paper itself

Abstract

Scientists increasingly recognize the importance of providing rich, standards-adherent metadata to describe their experimental results. Despite the availability of sophisticated tools to assist in the process of data annotation, investigators generally seem to prefer to use spreadsheets when supplying metadata, despite the limitations of spreadsheets in ensuring metadata consistency and compliance with formal specifications. In this paper, we describe an end-to-end approach that supports spreadsheet-based entry of metadata, while ensuring rigorous adherence to community-based metadata standards and providing quality control. Our methods employ several key components, including customizable templates that represent metadata standards and that can inform the spreadsheets that investigators use to author metadata, controlled terminologies and ontologies for defining metadata values that can be accessed directly from a spreadsheet, and an interactive Web-based tool that allows users to rapidly identify and fix errors in their spreadsheet-based metadata. We demonstrate how this approach is being deployed in a biomedical consortium known as HuBMAP to define and collect metadata about a wide range of biological assays.

Identifiers

PMID39952970
PMCPMC11828951

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.