Evidence map›Paper›PMID 34275487›Full record

ArticleJournal of biomedical semantics2021

The Infectious Disease Ontology in the age of COVID-19.

Shane Babcock, John Beverley, Lindsay G Cowell, Barry Smith

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical semantics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

32 citing papers in PubMed, 67 citations in OpenAlex.

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  5. A fourfold pathogen reference ontology suite.Journal of biomedical semantics · 2025
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  8. Review
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  13. Big knowledge visualization of the COVID-19 CIDO ontology evolution.BMC medical informatics and decision making · 2023
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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 3 institutions in 1 country.

Shane BabcockDepartment of Philosophy, Niagara University, Lewiston, NY, USA. sbabcock@niagara.edu.ORCID 0000-0003-0798-114X
John BeverleyNational Center for Ontological Research, University at Buffalo, Buffalo, NY, USA.
Lindsay G CowellNational Center for Ontological Research, University at Buffalo, Buffalo, NY, USA.
Barry SmithNational Center for Ontological Research, University at Buffalo, Buffalo, NY, USA.
University at Buffalo, State University of New York · USNiagara University · USNorthwestern University · US

Funding

University of Buffalo Clinical and Translational Science Institute - Supplement SchulyerUL1TR001412 · NCATS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MURPHY, TIMOTHY F · 2015 to 2024
$33.8M
National Library of Medicine Conference 2022T15LM012495 · NLM · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI PETER L. ELKIN · 2017 to 2026
$4.3M
NCATS NIH HHS 1UL1TR001412NCATS NIH HHS UL1 TR001412NIH HHS 5T15LM012495-03NLM NIH HHS T15 LM012495
6 · The paper itself

Abstract

backgroundEffective response to public health emergencies, such as we are now experiencing with COVID-19, requires data sharing across multiple disciplines and data systems. Ontologies offer a powerful data sharing tool, and this holds especially for those ontologies built on the design principles of the Open Biomedical Ontologies Foundry. These principles are exemplified by the Infectious Disease Ontology (IDO), a suite of interoperable ontology modules aiming to provide coverage of all aspects of the infectious disease domain. At its center is IDO Core, a disease- and pathogen-neutral ontology covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is extended by disease and pathogen-specific ontology modules.

resultsTo assist the integration and analysis of COVID-19 data, and viral infectious disease data more generally, we have recently developed three new IDO extensions: IDO Virus (VIDO); the Coronavirus Infectious Disease Ontology (CIDO); and an extension of CIDO focusing on COVID-19 (IDO-COVID-19). Reflecting the fact that viruses lack cellular parts, we have introduced into IDO Core the term acellular structure to cover viruses and other acellular entities studied by virologists. We now distinguish between infectious agents - organisms with an infectious disposition - and infectious structures - acellular structures with an infectious disposition. This in turn has led to various updates and refinements of IDO Core's content. We believe that our work on VIDO, CIDO, and IDO-COVID-19 can serve as a model for yielding greater conformance with ontology building best practices.

conclusionsIDO provides a simple recipe for building new pathogen-specific ontologies in a way that allows data about novel diseases to be easily compared, along multiple dimensions, with data represented by existing disease ontologies. The IDO strategy, moreover, supports ontology coordination, providing a powerful method of data integration and sharing that allows physicians, researchers, and public health organizations to respond rapidly and efficiently to current and future public health crises.

Indexed as

Biological OntologiesCommunicable Disease ControlCommunicable DiseasesComputational BiologyCOVID-19Data MiningEpidemicsHumansInformation DisseminationPublic HealthSARS-CoV-2SemanticsCoronavirusCOVID-19Data integrationInfectious diseaseInfectious disease ontologyOntology

Identifiers

PMID34275487
PMCPMC8286442
OpenAlexW3018965582

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.