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An efficient strategy for the collection and storage of large volumes of data for computation

Overview of attention for article published in Journal of Big Data, October 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
6 X users

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
56 Mendeley
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Title
An efficient strategy for the collection and storage of large volumes of data for computation
Published in
Journal of Big Data, October 2016
DOI 10.1186/s40537-016-0056-1
Authors

Uthayanath Suthakar, Luca Magnoni, David Ryan Smith, Akram Khan, Julia Andreeva

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 21%
Student > Ph. D. Student 11 20%
Student > Doctoral Student 5 9%
Researcher 3 5%
Other 3 5%
Other 9 16%
Unknown 13 23%
Readers by discipline Count As %
Computer Science 26 46%
Engineering 6 11%
Business, Management and Accounting 2 4%
Agricultural and Biological Sciences 2 4%
Social Sciences 2 4%
Other 5 9%
Unknown 13 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 07 December 2016.
All research outputs
#5,743,600
of 22,896,955 outputs
Outputs from Journal of Big Data
#91
of 336 outputs
Outputs of similar age
#87,151
of 313,854 outputs
Outputs of similar age from Journal of Big Data
#5
of 9 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 336 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.4. This one has gotten more attention than average, scoring higher than 72% 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 313,854 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 72% of its contemporaries.
We're also able to compare this research output to 9 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.