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X Demographics
Mendeley readers
Attention Score in Context
| Title |
OTO: Ontology Term Organizer
|
|---|---|
| Published in |
BMC Bioinformatics, February 2015
|
| DOI | 10.1186/s12859-015-0488-1 |
| Pubmed ID | |
| Authors |
Fengqiong Huang, James A Macklin, Hong Cui, Heather A Cole, Lorena Endara |
| Abstract |
The need to create controlled vocabularies such as ontologies for knowledge organization and access has been widely recognized in various domains. Despite the indispensable need of thorough domain knowledge in ontology construction, most software tools for ontology construction are designed for knowledge engineers and not for domain experts to use. The differences in the opinions of different domain experts and in the terminology usages in source literature are rarely addressed by existing software. OTO software was developed based on the Agile principles. Through iterations of software release and user feedback, new features are added and existing features modified to make the tool more intuitive and efficient to use for small and large data sets. The software is open source and built in Java. Ontology Term Organizer (OTO; http://biosemantics.arizona.edu/OTO/ ) is a user-friendly, web-based, consensus-promoting, open source application for organizing domain terms by dragging and dropping terms to appropriate locations. The application is designed for users with specific domain knowledge such as biology but not in-depth ontology construction skills. Specifically OTO can be used to establish is_a, part_of, synonym, and order relationships among terms in any domain that reflects the terminology usage in source literature and based on multiple experts' opinions. The organized terms may be fed into formal ontologies to boost their coverage. All datasets organized on OTO are publicly available. OTO has been used to organize the terms extracted from thirty volumes of Flora of North America and Flora of China combined, in addition to some smaller datasets of different taxon groups. User feedback indicates that the tool is efficient and user friendly. Being open source software, the application can be modified to fit varied term organization needs for different domains. |
X Demographics
The data shown below were collected from the profiles of 6 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 Kingdom | 1 | 17% |
| United States | 1 | 17% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 5% |
| Spain | 1 | 2% |
| United States | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 36 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 17% |
| Student > Master | 7 | 17% |
| Student > Bachelor | 5 | 12% |
| Student > Doctoral Student | 3 | 7% |
| Student > Ph. D. Student | 3 | 7% |
| Other | 11 | 27% |
| Unknown | 5 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 34% |
| Computer Science | 13 | 32% |
| Social Sciences | 3 | 7% |
| Medicine and Dentistry | 2 | 5% |
| Engineering | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 5 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 February 2015.
All research outputs
#7,454,951
of 22,790,780 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,280 outputs
Outputs of similar age
#118,432
of 385,323 outputs
Outputs of similar age from BMC Bioinformatics
#57
of 134 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% 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 385,323 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 134 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.