Evidence map›Paper›PMID 36856688›Full record

ArticleDatabase : the journal of biological databases and curation2023

Assessing resource use: a case study with the Human Disease Ontology.

J Allen Baron, Lynn M Schriml

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2023. 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

2 authors.

J Allen BaronUniversity of Maryland School of Medicine, Institute for Genome Sciences, 670 W. Baltimore St., HSFIII, Baltimore, MD 21201, USA.
Lynn M SchrimlUniversity of Maryland School of Medicine, Institute for Genome Sciences, 670 W. Baltimore St., HSFIII, Baltimore, MD 21201, USA.ORCID 0000-0001-8910-9851

Funding

The Human Disease Ontology: An integrated, mechanistic knowledge resource for biomedical research.U24HG012557 · NHGRI · UNIVERSITY OF MARYLAND BALTIMORE · PI Lynn Marie Schriml · 2022 to 2026
$3.7M
The Disease Ontology Project: mechanistic profiles of human disease for biomedical and clinical researchU41HG008735 · NHGRI · UNIVERSITY OF MARYLAND BALTIMORE · PI SCHRIML, LYNN MARIE · 2017 to 2021
$3.4M
NHGRI NIH HHS U24 HG012557NHGRI NIH HHS U41 HG008735
6 · The paper itself

Abstract

As a genomic resource provider, grappling with getting a handle on how your resource is utilized can be extremely challenging. At the same time, being able to thus document the plethora of use cases is vital to demonstrate sustainability. Herein, we describe a flexible workflow, built on readily available software, that the Human Disease Ontology (DO) project has utilized to transition to semi-automated methods to identify uses of the ontology in the published literature. The novel R package DO.utils (https://github.com/DiseaseOntology/DO.utils) has been devised with a small set of key functions to support our usage workflow in combination with Google Sheets. Use of this workflow has resulted in a 3-fold increase in the number of identified publications that use the DO and has provided novel usage insights that offer new research directions and reveal a clearer picture of the DO's use and scientific impact. The DO's resource use assessment workflow and the supporting software are designed to be useful to other resources, including databases, software tools, method providers and other web resources, to achieve similar results. Database URL: https://github.com/DiseaseOntology/DO.utils.

Indexed as

GenomicsSoftwareDatabases, FactualHumansWorkflow

Identifiers

PMID36856688
PMCPMC9972798

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.