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A multi-level security model for partitioning workflows over federated clouds

Overview of attention for article published in Journal of Cloud Computing, January 2012
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Title
A multi-level security model for partitioning workflows over federated clouds
Published in
Journal of Cloud Computing, January 2012
DOI 10.1186/2192-113x-1-15
Authors

Paul Watson

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 March 2020.
All research outputs
#9,760,039
of 15,341,807 outputs
Outputs from Journal of Cloud Computing
#66
of 160 outputs
Outputs of similar age
#156,623
of 265,827 outputs
Outputs of similar age from Journal of Cloud Computing
#1
of 1 outputs
Altmetric has tracked 15,341,807 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 160 research outputs from this source. They receive a mean Attention Score of 2.0. This one is in the 32nd percentile – i.e., 32% 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 265,827 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
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