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Building a semantic web-based metadata repository for facilitating detailed clinical modeling in cancer genome studies

Overview of attention for article published in Journal of Biomedical Semantics, June 2017
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Title
Building a semantic web-based metadata repository for facilitating detailed clinical modeling in cancer genome studies
Published in
Journal of Biomedical Semantics, June 2017
DOI 10.1186/s13326-017-0130-4
Pubmed ID
Authors

Deepak K. Sharma, Harold R. Solbrig, Cui Tao, Chunhua Weng, Christopher G. Chute, Guoqian Jiang

Abstract

Detailed Clinical Models (DCMs) have been regarded as the basis for retaining computable meaning when data are exchanged between heterogeneous computer systems. To better support clinical cancer data capturing and reporting, there is an emerging need to develop informatics solutions for standards-based clinical models in cancer study domains. The objective of the study is to develop and evaluate a cancer genome study metadata management system that serves as a key infrastructure in supporting clinical information modeling in cancer genome study domains. We leveraged a Semantic Web-based metadata repository enhanced with both ISO11179 metadata standard and Clinical Information Modeling Initiative (CIMI) Reference Model. We used the common data elements (CDEs) defined in The Cancer Genome Atlas (TCGA) data dictionary, and extracted the metadata of the CDEs using the NCI Cancer Data Standards Repository (caDSR) CDE dataset rendered in the Resource Description Framework (RDF). The ITEM/ITEM_GROUP pattern defined in the latest CIMI Reference Model is used to represent reusable model elements (mini-Archetypes). We produced a metadata repository with 38 clinical cancer genome study domains, comprising a rich collection of mini-Archetype pattern instances. We performed a case study of the domain "clinical pharmaceutical" in the TCGA data dictionary and demonstrated enriched data elements in the metadata repository are very useful in support of building detailed clinical models. Our informatics approach leveraging Semantic Web technologies provides an effective way to build a CIMI-compliant metadata repository that would facilitate the detailed clinical modeling to support use cases beyond TCGA in clinical cancer study domains.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 45 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 20%
Researcher 7 15%
Professor 6 13%
Student > Doctoral Student 3 7%
Student > Master 3 7%
Other 8 17%
Unknown 10 22%
Readers by discipline Count As %
Computer Science 16 35%
Medicine and Dentistry 6 13%
Biochemistry, Genetics and Molecular Biology 3 7%
Engineering 3 7%
Agricultural and Biological Sciences 2 4%
Other 5 11%
Unknown 11 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 June 2017.
All research outputs
#21,264,673
of 23,881,329 outputs
Outputs from Journal of Biomedical Semantics
#336
of 358 outputs
Outputs of similar age
#279,203
of 319,138 outputs
Outputs of similar age from Journal of Biomedical Semantics
#4
of 4 outputs
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So far Altmetric has tracked 358 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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