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CEDAR OnDemand: a browser extension to generate ontology-based scientific metadata

Overview of attention for article published in BMC Bioinformatics, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

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Title
CEDAR OnDemand: a browser extension to generate ontology-based scientific metadata
Published in
BMC Bioinformatics, July 2018
DOI 10.1186/s12859-018-2247-6
Pubmed ID
Authors

Syed Ahmad Chan Bukhari, Marcos Martínez-Romero, Martin J. O’ Connor, Attila L. Egyedi, Debra Willrett, John Graybeal, Mark A. Musen, Kei-Hoi Cheung, Steven H. Kleinstein

Abstract

Public biomedical data repositories often provide web-based interfaces to collect experimental metadata. However, these interfaces typically reflect the ad hoc metadata specification practices of the associated repositories, leading to a lack of standardization in the collected metadata. This lack of standardization limits the ability of the source datasets to be broadly discovered, reused, and integrated with other datasets. To increase reuse, discoverability, and reproducibility of the described experiments, datasets should be appropriately annotated by using agreed-upon terms, ideally from ontologies or other controlled term sources. This work presents "CEDAR OnDemand", a browser extension powered by the NCBO (National Center for Biomedical Ontology) BioPortal that enables users to seamlessly enter ontology-based metadata through existing web forms native to individual repositories. CEDAR OnDemand analyzes the web page contents to identify the text input fields and associate them with relevant ontologies which are recommended automatically based upon input fields' labels (using the NCBO ontology recommender) and a pre-defined list of ontologies. These field-specific ontologies are used for controlling metadata entry. CEDAR OnDemand works for any web form designed in the HTML format. We demonstrate how CEDAR OnDemand works through the NCBI (National Center for Biotechnology Information) BioSample web-based metadata entry. CEDAR OnDemand helps lower the barrier of incorporating ontologies into standardized metadata entry for public data repositories. CEDAR OnDemand is available freely on the Google Chrome store https://chrome.google.com/webstore/search/CEDAROnDemand.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 26%
Researcher 6 15%
Student > Master 3 8%
Student > Bachelor 3 8%
Professor 2 5%
Other 7 18%
Unknown 8 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 21%
Computer Science 6 15%
Biochemistry, Genetics and Molecular Biology 3 8%
Social Sciences 2 5%
Unspecified 2 5%
Other 8 21%
Unknown 10 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 November 2019.
All research outputs
#2,849,322
of 25,761,363 outputs
Outputs from BMC Bioinformatics
#795
of 7,743 outputs
Outputs of similar age
#54,785
of 340,703 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 99 outputs
Altmetric has tracked 25,761,363 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,743 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 340,703 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 99 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.