Evidence map›Paper›PMID 35106535›Full record

ArticleDatabase : the journal of biological databases and curation2022

Authors' attitude toward adopting a new workflow to improve the computability of phenotype publications.

Hong Cui, Bruce Ford, Julian Starr, Anton Reznicek, Limin Zhang, James A Macklin

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2022. 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
–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

1 citing paper in PubMed.

  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

6 authors.

Bruce Ford
Julian Starr
Anton Reznicek

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Critical to answering large-scale questions in biology is the integration of knowledge from different disciplines into a coherent, computable whole. Controlled vocabularies such as ontologies represent a clear path toward this goal. Using survey questionnaires, we examined the attitudes of biologists toward adopting controlled vocabularies in phenotype publications. Our questions cover current experience and overall attitude with controlled vocabularies, the awareness of the issues around ambiguity and inconsistency in phenotype descriptions and post-publication professional data curation, the preferred solutions and the effort and desired rewards for adopting a new authoring workflow. Results suggest that although the existence of controlled vocabularies is widespread, their use is not common. A majority of respondents (74%) are frustrated with ambiguity in phenotypic descriptions, and there is a strong agreement (mean agreement score 4.21 out of 5) that author curation would better reflect the original meaning of phenotype data. Moreover, the vast majority (85%) of researchers would try a new authoring workflow if resultant data were more consistent and less ambiguous. Even more respondents (93%) suggested that they would try and possibly adopt a new authoring workflow if it required 5% additional effort as compared to normal, but higher rates resulted in a steep decline in likely adoption rates. Among the four different types of rewards, two types of citations were the most desired incentives for authors to produce computable data. Overall, our results suggest the adoption of a new authoring workflow would be accelerated by a user-friendly and efficient software-authoring tool, an increased awareness of the challenges text ambiguity creates for external curators and an elevated appreciation of the benefits of controlled vocabularies.

Indexed as

Data CurationSoftwareAttitudePhenotypeWorkflow

Identifiers

PMID35106535
PMCPMC9278328

What Socratic 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 Socratic graph.