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Using Semantic Web technologies for the generation of domain-specific templates to support clinical study metadata standards

Overview of attention for article published in Journal of Biomedical Semantics, March 2016
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Title
Using Semantic Web technologies for the generation of domain-specific templates to support clinical study metadata standards
Published in
Journal of Biomedical Semantics, March 2016
DOI 10.1186/s13326-016-0053-5
Pubmed ID
Authors

Guoqian Jiang, Julie Evans, Cory M. Endle, Harold R. Solbrig, Christopher G. Chute

Abstract

The Biomedical Research Integrated Domain Group (BRIDG) model is a formal domain analysis model for protocol-driven biomedical research, and serves as a semantic foundation for application and message development in the standards developing organizations (SDOs). The increasing sophistication and complexity of the BRIDG model requires new approaches to the management and utilization of the underlying semantics to harmonize domain-specific standards. The objective of this study is to develop and evaluate a Semantic Web-based approach that integrates the BRIDG model with ISO 21090 data types to generate domain-specific templates to support clinical study metadata standards development. We developed a template generation and visualization system based on an open source Resource Description Framework (RDF) store backend, a SmartGWT-based web user interface, and a "mind map" based tool for the visualization of generated domain-specific templates. We also developed a RESTful Web Service informed by the Clinical Information Modeling Initiative (CIMI) reference model for access to the generated domain-specific templates. A preliminary usability study is performed and all reviewers (n = 3) had very positive responses for the evaluation questions in terms of the usability and the capability of meeting the system requirements (with the average score of 4.6). Semantic Web technologies provide a scalable infrastructure and have great potential to enable computable semantic interoperability of models in the intersection of health care and clinical research.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Unknown 56 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 19%
Student > Ph. D. Student 9 16%
Researcher 4 7%
Student > Postgraduate 4 7%
Student > Doctoral Student 4 7%
Other 16 28%
Unknown 9 16%
Readers by discipline Count As %
Computer Science 22 39%
Social Sciences 7 12%
Agricultural and Biological Sciences 4 7%
Nursing and Health Professions 4 7%
Medicine and Dentistry 4 7%
Other 6 11%
Unknown 10 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 10 March 2016.
All research outputs
#14,712,301
of 22,852,911 outputs
Outputs from Journal of Biomedical Semantics
#223
of 364 outputs
Outputs of similar age
#165,369
of 298,620 outputs
Outputs of similar age from Journal of Biomedical Semantics
#7
of 8 outputs
Altmetric has tracked 22,852,911 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 38th percentile – i.e., 38% 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 298,620 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one.