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A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience

Overview of attention for article published in BMC Medical Informatics and Decision Making, October 2012
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Mentioned by

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4 X users

Citations

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9 Dimensions

Readers on

mendeley
62 Mendeley
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1 CiteULike
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Title
A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience
Published in
BMC Medical Informatics and Decision Making, October 2012
DOI 10.1186/1472-6947-12-115
Pubmed ID
Authors

Luca Corradi, Ivan Porro, Andrea Schenone, Parastoo Momeni, Raffaele Ferrari, Flavio Nobili, Michela Ferrara, Gabriele Arnulfo, Marco M Fato

Abstract

Robust, extensible and distributed databases integrating clinical, imaging and molecular data represent a substantial challenge for modern neuroscience. It is even more difficult to provide extensible software environments able to effectively target the rapidly changing data requirements and structures of research experiments. There is an increasing request from the neuroscience community for software tools addressing technical challenges about: (i) supporting researchers in the medical field to carry out data analysis using integrated bioinformatics services and tools; (ii) handling multimodal/multiscale data and metadata, enabling the injection of several different data types according to structured schemas; (iii) providing high extensibility, in order to address different requirements deriving from a large variety of applications simply through a user runtime configuration.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Italy 1 2%
Unknown 60 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 21%
Student > Ph. D. Student 7 11%
Librarian 5 8%
Student > Master 5 8%
Student > Bachelor 4 6%
Other 14 23%
Unknown 14 23%
Readers by discipline Count As %
Computer Science 14 23%
Medicine and Dentistry 8 13%
Engineering 5 8%
Agricultural and Biological Sciences 4 6%
Arts and Humanities 3 5%
Other 12 19%
Unknown 16 26%
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 24 August 2017.
All research outputs
#13,873,556
of 22,681,577 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,065
of 1,979 outputs
Outputs of similar age
#97,299
of 172,974 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#32
of 45 outputs
Altmetric has tracked 22,681,577 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,979 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 44th percentile – i.e., 44% 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 172,974 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.