Evidence map›Paper›PMID 32790700›Full record

ArticlePloS one2020

A rapid and cost-effective pipeline for digitization of museum specimens with 3D photogrammetry.

Joshua J Medina, James M Maley, Siddharth Sannapareddy, Noah N Medina, Cyril M Gilman, John E McCormack

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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  12. Opportunities and Challenges in Applying AI to Evolutionary Morphology.Integrative organismal biology (Oxford, England) · 2024
    Review
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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

6 authors.

Joshua J MedinaMoore Laboratory of Zoology, Occidental College, Los Angeles, CA, United States of America.
James M MaleyMoore Laboratory of Zoology, Occidental College, Los Angeles, CA, United States of America.
Siddharth SannapareddyMoore Laboratory of Zoology, Occidental College, Los Angeles, CA, United States of America.
Noah N MedinaMoore Laboratory of Zoology, Occidental College, Los Angeles, CA, United States of America.
Cyril M GilmanMoore Laboratory of Zoology, Occidental College, Los Angeles, CA, United States of America.
John E McCormackMoore Laboratory of Zoology, Occidental College, Los Angeles, CA, United States of America.ORCID 0000-0002-0912-1461

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural history collections are yielding more information as digitization brings specimen data to researchers, connects specimens across museums, and as new technologies allow for more large-scale data collection. Therefore, a key goal in specimen digitization is developing methods that both increase access and allow for the highest yield of phenomic data. 3D digitization is increasingly popular because it has the potential to meet both aspects of that key goal. However, current methods overlook or do not prioritize some of the most sought-after phenotypic traits, those involving the external appearance of specimens, especially color. Here, we introduce an efficient and cost-effective pipeline for 3D photogrammetry to capture the external appearance of natural history specimens and other museum objects. 3D photogrammetry aligns and compares sets of dozens, hundreds, or even thousands of photos to create 3D models. The hardware set-up requires little physical space and around $3,000 in initial investment, while the software pipeline requires $1,400/year for proprietary software subscriptions (with open-source alternatives). The creation of each 3D model takes 1-2 hours/specimen and much of the software pipeline is automated with minimal supervision required, including the onerous step of mesh processing. We showcase the method by creating 3D models for most of the type specimens in the Moore Laboratory of Zoology bird collection and show that digital bill measurements are comparable to hand-taken measurements. Color data, while not included as part of this pipeline, is easily extractable from the models and one of the most promising areas of data collection. Future advances can adapt the method for ultraviolet reflectance capture and increased efficiency and model quality. Combined with genomic data, phenomic data from 3D models including photogrammetry will open new doors to understanding organismal evolution.

Indexed as

MuseumsAnimalsBirdsCost-Benefit AnalysisImaging, Three-DimensionalNatural HistoryPhotogrammetrySoftwareTime FactorsWorkflow

Identifiers

PMID32790700
PMCPMC7425849

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LicenceCC BY
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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.