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Toward an execution system for self-healing workflows in cyber-physical systems

Overview of attention for article published in Software and Systems Modeling, August 2016
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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2 X users

Citations

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51 Dimensions

Readers on

mendeley
89 Mendeley
Title
Toward an execution system for self-healing workflows in cyber-physical systems
Published in
Software and Systems Modeling, August 2016
DOI 10.1007/s10270-016-0551-z
Authors

Ronny Seiger, Steffen Huber, Thomas Schlegel

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 1%
Unknown 88 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 24%
Student > Ph. D. Student 17 19%
Professor 6 7%
Student > Bachelor 5 6%
Researcher 4 4%
Other 10 11%
Unknown 26 29%
Readers by discipline Count As %
Computer Science 42 47%
Engineering 12 13%
Business, Management and Accounting 3 3%
Economics, Econometrics and Finance 1 1%
Agricultural and Biological Sciences 1 1%
Other 0 0%
Unknown 30 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 01 September 2016.
All research outputs
#16,937,429
of 25,878,862 outputs
Outputs from Software and Systems Modeling
#295
of 559 outputs
Outputs of similar age
#243,129
of 383,944 outputs
Outputs of similar age from Software and Systems Modeling
#6
of 10 outputs
Altmetric has tracked 25,878,862 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 559 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 42nd percentile – i.e., 42% 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 383,944 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.