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Ontological anti-patterns: empirically uncovered error-prone structures in ontology-driven conceptual models

Overview of attention for article published in Data & Knowledge Engineering, September 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)

Mentioned by

wikipedia
1 Wikipedia page

Readers on

mendeley
90 Mendeley
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Article details
Title
Ontological anti-patterns: empirically uncovered error-prone structures in ontology-driven conceptual models
Published in
Data & Knowledge Engineering, September 2015
DOI 10.1016/j.datak.2015.06.004
Authors

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Timeline Attention over time Attention Score history
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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Germany 1 1%
Brazil 1 1%
Belgium 1 1%
Unknown 87 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 22 24%
Student > Master 13 14%
Student > Doctoral Student 8 9%
Researcher 7 8%
Professor > Associate Professor 6 7%
Other 18 20%
Unknown 16 18%
Readers by discipline
Readers by discipline Count As %
Computer Science 53 59%
Engineering 8 9%
Business, Management and Accounting 4 4%
Arts and Humanities 2 2%
Medicine and Dentistry 2 2%
Other 5 6%
Unknown 16 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 16 May 2020.
All research outputs
#9,514,305
of 27,774,969 outputs
Outputs from Data & Knowledge Engineering
#78
of 388 outputs
Outputs of similar age
#98,728
of 279,126 outputs
Outputs of similar age from Data & Knowledge Engineering
#2
of 3 outputs
Altmetric has tracked 27,774,969 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 388 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 279,126 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.