Evidence map›Paper›PMID 31437939›Full record

ArticleStudies in health technology and informatics2019

Semantic Provenance Graph for Reproducibility of Biomedical Research Studies: Generating and Analyzing Graph Structures from Published Literature.

Satya S Sahoo, Joshua Valdez, Michael Rueschman, Matthew Kim

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Studies in health technology and informatics, 2019. 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
0.3field-weighted citation impact, top 39% of its field
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, 2 citations in OpenAlex.

  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

4 authors at 2 institutions in 1 country.

Satya S SahooDepartment of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
Joshua ValdezDepartment of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Harvard University, Boston, MA, USA.
Michael RueschmanDepartment of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Harvard University, Boston, MA, USA.
Matthew KimDepartment of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Harvard University, Boston, MA, USA.
Beth Israel Deaconess Medical Center · USCase Western Reserve University · US

Funding

A PROV standard-based data source agnostic provenance engine for Big Data analytics (Supplement)U01EB020955 · NIBIB · CASE WESTERN RESERVE UNIVERSITY · PI SAHOO, SATYA SANKET · 2015 to 2017
$1.0M
NIBIB NIH HHS U01 EB020955
6 · The paper itself

Abstract

objectiveTo characterize the scientific reproducibility of biomedical research studies by query and analysis of semantic provenance graphs generated from provenance metadata terms extracted from PubMed articles.

methodsWe develop a new semantic provenance graph generation algorithm that uses a provenance ontology developed as part of the Provenance for Clinical and Health Research (ProvCaRe) project. The ProvCaRe project has processed and extracted provenance metadata from more than 1.6 million full text articles from the PubMed database.

resultsThe semantic provenance graph generation algorithm is evaluated using provenance terms extracted from 75 selected articles describing sleep medicine research studies. In addition, we use eight provenance queries to evaluate the quality of semantic provenance graphs generated by the new algorithm.

conclusionThe ProvCaRe project has created a unique resource to characterize the reproducibility of biomedical research studies and the semantic provenance graph generation algorithm enables users to effectively query and analyze the provenance metadata in the ProvCaRe knowledge repository.

Indexed as

Biological OntologiesBiomedical ResearchMetadataReproducibility of ResultsSemanticsBiomedical OntologiesHealth Information SystemsKnowledge Bases

Identifiers

PMID31437939
PMCPMC6800194
OpenAlexW2979079860

What OpenQuestion holds

Textmetadata
LicenceTDM
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.