You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
Attention Score in Context
| Title |
Standards-based metadata procedures for retrieving data for display or mining utilizing persistent (data-DOI) identifiers
|
|---|---|
| Published in |
Journal of Cheminformatics, August 2015
|
| DOI | 10.1186/s13321-015-0081-7 |
| Pubmed ID | |
| Authors |
Matthew J Harvey, Nicholas J Mason, Andrew McLean, Henry S Rzepa |
| Abstract |
We describe three different procedures based on metadata standards for enabling automated retrieval of scientific data from digital repositories utilising the persistent identifier of the dataset with optional specification of the attributes of the data document such as filename or media type. The procedures are demonstrated using the JSmol molecular visualizer as a component of a web page and Avogadro as a stand-alone modelling program. We compare our methods for automated retrieval of data from a standards-compliant data repository with those currently in operation for a selection of existing molecular databases and repositories. Our methods illustrate the importance of adopting a standards-based approach of using metadata declarations to increase access to and discoverability of repository-based data. Graphical abstract. |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| Germany | 1 | 4% |
| Unknown | 22 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Librarian | 4 | 17% |
| Student > Ph. D. Student | 3 | 13% |
| Researcher | 3 | 13% |
| Student > Master | 3 | 13% |
| Student > Doctoral Student | 2 | 8% |
| Other | 6 | 25% |
| Unknown | 3 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 7 | 29% |
| Social Sciences | 3 | 13% |
| Environmental Science | 2 | 8% |
| Physics and Astronomy | 2 | 8% |
| Chemistry | 2 | 8% |
| Other | 4 | 17% |
| Unknown | 4 | 17% |
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 05 January 2016.
All research outputs
#5,554,632
of 22,986,950 outputs
Outputs from Journal of Cheminformatics
#458
of 841 outputs
Outputs of similar age
#63,562
of 264,870 outputs
Outputs of similar age from Journal of Cheminformatics
#8
of 15 outputs
Altmetric has tracked 22,986,950 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 841 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 45th percentile – i.e., 45% 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 264,870 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 75% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.