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TheHiveDB image data management and analysis framework

Overview of attention for article published in Frontiers in Neuroinformatics, January 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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53 Mendeley
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Title
TheHiveDB image data management and analysis framework
Published in
Frontiers in Neuroinformatics, January 2014
DOI 10.3389/fninf.2013.00049
Pubmed ID
Authors

J-Sebastian Muehlboeck, Eric Westman, Andrew Simmons

Abstract

The hive database system (theHiveDB) is a web-based brain imaging database, collaboration, and activity system which has been designed as an imaging workflow management system capable of handling cross-sectional and longitudinal multi-center studies. It can be used to organize and integrate existing data from heterogeneous projects as well as data from ongoing studies. It has been conceived to guide and assist the researcher throughout the entire research process, integrating all relevant types of data across modalities (e.g., brain imaging, clinical, and genetic data). TheHiveDB is a modern activity and resource management system capable of scheduling image processing on both private compute resources and the cloud. The activity component supports common image archival and management tasks as well as established pipeline processing (e.g., Freesurfer for extraction of scalar measures from magnetic resonance images). Furthermore, via theHiveDB activity system algorithm developers may grant access to virtual machines hosting versioned releases of their tools to collaborators and the imaging community. The application of theHiveDB is illustrated with a brief use case based on organizing, processing, and analyzing data from the publically available Alzheimer Disease Neuroimaging Initiative.

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X Demographics

The data shown below were collected from the profiles of 5 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 2%
Unknown 52 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 21%
Student > Master 10 19%
Researcher 7 13%
Professor 4 8%
Professor > Associate Professor 4 8%
Other 8 15%
Unknown 9 17%
Readers by discipline Count As %
Psychology 8 15%
Medicine and Dentistry 6 11%
Computer Science 6 11%
Neuroscience 6 11%
Engineering 4 8%
Other 8 15%
Unknown 15 28%
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 27 August 2020.
All research outputs
#5,676,934
of 23,590,588 outputs
Outputs from Frontiers in Neuroinformatics
#267
of 774 outputs
Outputs of similar age
#64,246
of 308,590 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#9
of 22 outputs
Altmetric has tracked 23,590,588 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 774 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has gotten more attention than average, scoring higher than 65% 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 308,590 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.