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Computational storage: an efficient and scalable platform for big data and HPC applications

Overview of attention for article published in Journal of Big Data, November 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
1 X user
patent
2 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
39 Mendeley
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Title
Computational storage: an efficient and scalable platform for big data and HPC applications
Published in
Journal of Big Data, November 2019
DOI 10.1186/s40537-019-0265-5
Authors

Mahdi Torabzadehkashi, Siavash Rezaei, Ali HeydariGorji, Hosein Bobarshad, Vladimir Alves, Nader Bagherzadeh

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 21%
Student > Master 4 10%
Professor 4 10%
Researcher 3 8%
Student > Bachelor 2 5%
Other 5 13%
Unknown 13 33%
Readers by discipline Count As %
Computer Science 12 31%
Engineering 6 15%
Business, Management and Accounting 3 8%
Agricultural and Biological Sciences 1 3%
Arts and Humanities 1 3%
Other 2 5%
Unknown 14 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 19 April 2023.
All research outputs
#4,630,264
of 23,253,955 outputs
Outputs from Journal of Big Data
#85
of 350 outputs
Outputs of similar age
#92,313
of 358,866 outputs
Outputs of similar age from Journal of Big Data
#4
of 17 outputs
Altmetric has tracked 23,253,955 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 350 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has done well, scoring higher than 76% 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 358,866 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 74% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.