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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Colil: a database and search service for citation contexts in the life sciences domain
|
|---|---|
| Published in |
Journal of Biomedical Semantics, October 2015
|
| DOI | 10.1186/s13326-015-0037-x |
| Pubmed ID | |
| Authors |
Toyofumi Fujiwara, Yasunori Yamamoto |
| Abstract |
To promote research activities in a particular research area, it is important to efficiently identify current research trends, advances, and issues in that area. Although review papers in the research area can suffice for this purpose in general, researchers are not necessarily able to obtain these papers from research aspects of their interests at the time they are required. Therefore, the utilization of the citation contexts of papers in a research area has been considered as another approach. However, there are few search services to retrieve citation contexts in the life sciences domain; furthermore, efficiently obtaining citation contexts is becoming difficult due to the large volume and rapid growth of life sciences papers. Here, we introduce the Colil (Comments on Literature in Literature) database to store citation contexts in the life sciences domain. By using the Resource Description Framework (RDF) and a newly compiled vocabulary, we built the Colil database and made it available through the SPARQL endpoint. In addition, we developed a web-based search service called Colil that searches for a cited paper in the Colil database and then returns a list of citation contexts for it along with papers relevant to it based on co-citations. The citation contexts in the Colil database were extracted from full-text papers of the PubMed Central Open Access Subset (PMC-OAS), which includes 545,147 papers indexed in PubMed. These papers are distributed across 3,171 journals and cite 5,136,741 unique papers that correspond to approximately 25 % of total PubMed entries. By utilizing Colil, researchers can easily refer to a set of citation contexts and relevant papers based on co-citations for a target paper. Colil helps researchers to comprehend life sciences papers in a research area more efficiently and makes their biological research more efficient. |
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 | 2 | 20% |
| France | 1 | 10% |
| Unknown | 7 | 70% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 3% |
| Spain | 1 | 3% |
| Unknown | 30 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 19% |
| Researcher | 5 | 16% |
| Student > Bachelor | 4 | 13% |
| Professor | 3 | 9% |
| Student > Doctoral Student | 2 | 6% |
| Other | 7 | 22% |
| Unknown | 5 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 8 | 25% |
| Agricultural and Biological Sciences | 6 | 19% |
| Social Sciences | 3 | 9% |
| Unspecified | 2 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 8 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 02 October 2023.
All research outputs
#3,610,699
of 25,728,855 outputs
Outputs from Journal of Biomedical Semantics
#51
of 368 outputs
Outputs of similar age
#47,584
of 296,095 outputs
Outputs of similar age from Journal of Biomedical Semantics
#1
of 3 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 85% 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 296,095 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 83% of its contemporaries.
We're also able to compare this research output to 3 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