| Title |
Sharing Heterogeneous Data: The National Database for Autism Research
|
|---|---|
| Published in |
Neuroinformatics, May 2012
|
| DOI | 10.1007/s12021-012-9151-4 |
| Pubmed ID | |
| Authors |
Dan Hall, Michael F. Huerta, Matthew J. McAuliffe, Gregory K. Farber |
| Abstract |
The National Database for Autism Research (NDAR) is a secure research data repository designed to promote scientific data sharing and collaboration among autism spectrum disorder investigators. The goal of the project is to accelerate scientific discovery through data sharing, data harmonization, and the reporting of research results. Data from over 25,000 research participants are available to qualified investigators through the NDAR portal. Summary information about the available data is available to everyone through that portal. |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 13% |
| United Kingdom | 2 | 13% |
| Sweden | 1 | 7% |
| Brazil | 1 | 7% |
| Spain | 1 | 7% |
| Ireland | 1 | 7% |
| Unknown | 7 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 67% |
| Scientists | 5 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Unknown | 83 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 15% |
| Student > Master | 13 | 15% |
| Student > Ph. D. Student | 12 | 14% |
| Professor | 7 | 8% |
| Student > Doctoral Student | 6 | 7% |
| Other | 20 | 24% |
| Unknown | 13 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 17 | 20% |
| Computer Science | 12 | 14% |
| Medicine and Dentistry | 9 | 11% |
| Neuroscience | 7 | 8% |
| Engineering | 6 | 7% |
| Other | 13 | 15% |
| Unknown | 20 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 16 November 2017.
All research outputs
#3,422,592
of 25,654,806 outputs
Outputs from Neuroinformatics
#43
of 432 outputs
Outputs of similar age
#21,762
of 178,353 outputs
Outputs of similar age from Neuroinformatics
#1
of 5 outputs
Altmetric has tracked 25,654,806 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 432 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 90% 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 178,353 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 87% of its contemporaries.
We're also able to compare this research output to 5 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