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eNanoMapper: harnessing ontologies to enable data integration for nanomaterial risk assessment

Overview of attention for article published in Journal of Biomedical Semantics, March 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#3 of 356)
  • High Attention Score compared to outputs of the same age (96th percentile)

Mentioned by

blogs
2 blogs
twitter
44 tweeters
googleplus
1 Google+ user
reddit
1 Redditor

Citations

dimensions_citation
38 Dimensions

Readers on

mendeley
59 Mendeley
citeulike
5 CiteULike
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Title
eNanoMapper: harnessing ontologies to enable data integration for nanomaterial risk assessment
Published in
Journal of Biomedical Semantics, March 2015
DOI 10.1186/s13326-015-0005-5
Pubmed ID
Authors

Janna Hastings, Nina Jeliazkova, Gareth Owen, Georgia Tsiliki, Cristian R Munteanu, Christoph Steinbeck, Egon Willighagen

Abstract

Engineered nanomaterials (ENMs) are being developed to meet specific application needs in diverse domains across the engineering and biomedical sciences (e.g. drug delivery). However, accompanying the exciting proliferation of novel nanomaterials is a challenging race to understand and predict their possibly detrimental effects on human health and the environment. The eNanoMapper project (www.enanomapper.net) is creating a pan-European computational infrastructure for toxicological data management for ENMs, based on semantic web standards and ontologies. Here, we describe the development of the eNanoMapper ontology based on adopting and extending existing ontologies of relevance for the nanosafety domain. The resulting eNanoMapper ontology is available at http://purl.enanomapper.net/onto/enanomapper.owl. We aim to make the re-use of external ontology content seamless and thus we have developed a library to automate the extraction of subsets of ontology content and the assembly of the subsets into an integrated whole. The library is available (open source) at http://github.com/enanomapper/slimmer/. Finally, we give a comprehensive survey of the domain content and identify gap areas. ENM safety is at the boundary between engineering and the life sciences, and at the boundary between molecular granularity and bulk granularity. This creates challenges for the definition of key entities in the domain, which we also discuss.

Twitter Demographics

The data shown below were collected from the profiles of 44 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 7%
Bulgaria 1 2%
Netherlands 1 2%
Spain 1 2%
Germany 1 2%
Unknown 51 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 41%
Student > Ph. D. Student 9 15%
Other 6 10%
Student > Master 5 8%
Professor > Associate Professor 2 3%
Other 4 7%
Unknown 9 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 17%
Computer Science 8 14%
Environmental Science 7 12%
Engineering 6 10%
Chemistry 5 8%
Other 12 20%
Unknown 11 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 49. 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 22 September 2020.
All research outputs
#523,804
of 17,355,315 outputs
Outputs from Journal of Biomedical Semantics
#3
of 356 outputs
Outputs of similar age
#8,884
of 230,055 outputs
Outputs of similar age from Journal of Biomedical Semantics
#1
of 1 outputs
Altmetric has tracked 17,355,315 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 356 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done particularly well, scoring higher than 99% 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 230,055 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them