Evidence map›Paper›PMID 39979334›Full record

ArticleScientific data2025

Using a units ontology to annotate pre-existing metadata.

John H Porter, Margaret O'Brien, Marina Frants, Stevan Earl, Mary Martin, Christine M Laney

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

John H PorterUniversity of Virginia, Charlottesville, Virginia, USA. jhp7e@virginia.edu.ORCID http://orcid.org/0000-0003-3118-5784
Margaret O'BrienUniversity of California, Santa Barbara, Santa Barbara, California, USA.
Marina FrantsScripps Institution of Oceanography, La Jolla, California, USA.
Stevan EarlArizona State University, Tempe, Arizona, USA.
Mary MartinUniversity of New Hampshire, Durham, New Hampshire, USA.
Christine M LaneyNational Ecological Observatory Network (NEON), Battelle, Boulder, Colorado, USA.

Funding

Department of the Interior | Bureau of Ocean Energy Management (BOEM) MC15 AC00006National Aeronautics and Space Administration (NASA) NNX14 AR62 ANational Science Foundation (NSF) 1831937NSF | BIO | Division of Biological Infrastructure (DBI) 2217817, 1724433NSF | BIO | Division of Environmental Biology (DEB) 1637685, 2224545, 1724433NSF | BIO | Division of Environmental Biology (DEB) 1832221NSF | BIO | Division of Environmental Biology (DEB) 2224662NSF | GEO | Division of Ocean Sciences (OCE) 2224726
6 · The paper itself

Abstract

Automated processing of environmental data is hindered by the wide array of unit representations provided in the metadata of digital datasets. For example, gm/m2, g/m2, gm-2, g/m^2, g.m-2 and gramPerMeterSquared are all representations of a single complex unit that might be human-readable but are not machine-interpretable. Connecting ad hoc units to a single unit concept in an ontology permits the identification of datasets sharing units and provides additional information regarding labels, definitions, dimensions and transformations provided in the ontology. Here we use successive string transformations to link ad hoc unit representations to units in the QUDT ontology (e.g., unit: GM-PER-M2). Although only 896 of 7,110 distinct units in a corpus of ecological metadata from DataONE, the Environmental Data Initiative and the U.S. National Ecological Observatory Network were matched, 324,811 unit uses (instances) out of 355,057 of total unit uses were successfully mapped to QUDT units (91%). The resulting lookup table was used to enable a web service and R functions for adding annotation elements to Ecological Metadata Language documents.

Identifiers

PMID39979334
PMCPMC11842773

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Textmetadata
LicenceCC BY
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Registered trials

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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.