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

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

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: 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. Methods: 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). Results: 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. Conclusion: 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.

Original languageEnglish (US)
Article number19
JournalJournal of Biomedical Semantics
Volume8
Issue number1
DOIs
StatePublished - Jun 5 2017

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Keywords

  • Cancer Studies
  • Clinical Information Modeling Initiative (CIMI)
  • Common Data Elements (CDEs)
  • Detailed Clinical Models (DCMs)
  • Semantic Web Technologies
  • The Cancer Genome Atlas (TCGA)

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Health Informatics
  • Computer Networks and Communications

Cite this

Building a semantic web-based metadata repository for facilitating detailed clinical modeling in cancer genome studies. / Sharma, Deepak K.; Solbrig, Harold R.; Tao, Cui; Weng, Chunhua; Chute, Christopher G.; Jiang, Guoqian D.

In: Journal of Biomedical Semantics, Vol. 8, No. 1, 19, 05.06.2017.

Research output: Contribution to journalArticle

Sharma, Deepak K. ; Solbrig, Harold R. ; Tao, Cui ; Weng, Chunhua ; Chute, Christopher G. ; Jiang, Guoqian D. / Building a semantic web-based metadata repository for facilitating detailed clinical modeling in cancer genome studies. In: Journal of Biomedical Semantics. 2017 ; Vol. 8, No. 1.
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abstract = "Background: 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. Methods: 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). Results: 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. Conclusion: 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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