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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
SPANG: a SPARQL client supporting generation and reuse of queries for distributed RDF databases
|
|---|---|
| Published in |
BMC Bioinformatics, February 2017
|
| DOI | 10.1186/s12859-017-1531-1 |
| Pubmed ID | |
| Authors |
Hirokazu Chiba, Ikuo Uchiyama |
| Abstract |
Toward improved interoperability of distributed biological databases, an increasing number of datasets have been published in the standardized Resource Description Framework (RDF). Although the powerful SPARQL Protocol and RDF Query Language (SPARQL) provides a basis for exploiting RDF databases, writing SPARQL code is burdensome for users including bioinformaticians. Thus, an easy-to-use interface is necessary. We developed SPANG, a SPARQL client that has unique features for querying RDF datasets. SPANG dynamically generates typical SPARQL queries according to specified arguments. It can also call SPARQL template libraries constructed in a local system or published on the Web. Further, it enables combinatorial execution of multiple queries, each with a distinct target database. These features facilitate easy and effective access to RDF datasets and integrative analysis of distributed data. SPANG helps users to exploit RDF datasets by generation and reuse of SPARQL queries through a simple interface. This client will enhance integrative exploitation of biological RDF datasets distributed across the Web. This software package is freely available at http://purl.org/net/spang . |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 3 | 30% |
| Switzerland | 2 | 20% |
| Sweden | 1 | 10% |
| United States | 1 | 10% |
| Unknown | 3 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 70% |
| Scientists | 3 | 30% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 5% |
| Unknown | 20 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 24% |
| Researcher | 4 | 19% |
| Student > Master | 3 | 14% |
| Student > Doctoral Student | 2 | 10% |
| Student > Bachelor | 2 | 10% |
| Other | 5 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 7 | 33% |
| Agricultural and Biological Sciences | 6 | 29% |
| Unspecified | 2 | 10% |
| Engineering | 2 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 1 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 01 February 2018.
All research outputs
#4,092,100
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#1,551
of 7,387 outputs
Outputs of similar age
#82,712
of 422,264 outputs
Outputs of similar age from BMC Bioinformatics
#29
of 147 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,387 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 78% 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 422,264 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 80% of its contemporaries.
We're also able to compare this research output to 147 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.