| Title |
The NIFSTD and BIRNLex Vocabularies: Building Comprehensive Ontologies for Neuroscience
|
|---|---|
| Published in |
Neuroinformatics, October 2008
|
| DOI | 10.1007/s12021-008-9032-z |
| Pubmed ID | |
| Authors |
William J. Bug, Giorgio A. Ascoli, Jeffrey S. Grethe, Amarnath Gupta, Christine Fennema-Notestine, Angela R. Laird, Stephen D. Larson, Daniel Rubin, Gordon M. Shepherd, Jessica A. Turner, Maryann E. Martone |
| Abstract |
A critical component of the Neuroscience Information Framework (NIF) project is a consistent, flexible terminology for describing and retrieving neuroscience-relevant resources. Although the original NIF specification called for a loosely structured controlled vocabulary for describing neuroscience resources, as the NIF system evolved, the requirement for a formally structured ontology for neuroscience with sufficient granularity to describe and access a diverse collection of information became obvious. This requirement led to the NIF standardized (NIFSTD) ontology, a comprehensive collection of common neuroscience domain terminologies woven into an ontologically consistent, unified representation of the biomedical domains typically used to describe neuroscience data (e.g., anatomy, cell types, techniques), as well as digital resources (tools, databases) being created throughout the neuroscience community. NIFSTD builds upon a structure established by the BIRNLex, a lexicon of concepts covering clinical neuroimaging research developed by the Biomedical Informatics Research Network (BIRN) project. Each distinct domain module is represented using the Web Ontology Language (OWL). As much as has been practical, NIFSTD reuses existing community ontologies that cover the required biomedical domains, building the more specific concepts required to annotate NIF resources. By following this principle, an extensive vocabulary was assembled in a relatively short period of time for NIF information annotation, organization, and retrieval, in a form that promotes easy extension and modification. We report here on the structure of the NIFSTD, and its predecessor BIRNLex, the principles followed in its construction and provide examples of its use within NIF. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 15 | 11% |
| Germany | 2 | 1% |
| Spain | 2 | 1% |
| Malaysia | 1 | <1% |
| Denmark | 1 | <1% |
| Australia | 1 | <1% |
| Brazil | 1 | <1% |
| Russia | 1 | <1% |
| Unknown | 113 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 35 | 26% |
| Student > Ph. D. Student | 25 | 18% |
| Student > Bachelor | 14 | 10% |
| Professor > Associate Professor | 12 | 9% |
| Other | 9 | 7% |
| Other | 28 | 20% |
| Unknown | 14 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 46 | 34% |
| Computer Science | 27 | 20% |
| Neuroscience | 11 | 8% |
| Medicine and Dentistry | 10 | 7% |
| Psychology | 7 | 5% |
| Other | 19 | 14% |
| Unknown | 17 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 27 October 2015.
All research outputs
#4,513,608
of 22,789,566 outputs
Outputs from Neuroinformatics
#79
of 404 outputs
Outputs of similar age
#16,777
of 92,216 outputs
Outputs of similar age from Neuroinformatics
#3
of 10 outputs
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So far Altmetric has tracked 404 research outputs from this source. They receive a mean Attention Score of 4.5. This one has done well, scoring higher than 79% of its peers.
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