A semantic framework for data quality assurance in medical research

Lingkai Zhu; Helen Chen; Kevin Quach

A semantic framework for data quality assurance in medical research

Lingkai Zhu, Helen Chen, Kevin Quach

Bloomberg School of Public Health

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

The large amount of patient data amassed in the Electronic Patient Record systems are of great value for medical research. Aggregating research-grade data from these systems is a laborious, often manual process. We present a semantic framework that incorporates a data semantic model and validation rules to accelerate the cleansing process for data in Electronic Patient Record systems. We demonstrate the advantages of this semantic approach in assuring data quality over traditional data analysis methods.

Original language	English (US)
Pages (from-to)	54-55
Number of pages	2
Journal	CEUR Workshop Proceedings
Volume	1054
State	Published - Jan 1 2013
Event	4th Canadian Semantic Web Symposium, CSWS 2013 - Part of the Semantic Trilogy 2013 - Montreal, Canada Duration: Jul 10 2013 → …

Keywords

Data quality assurance
Data quality measurement
Ontology modelling
Semantic framework
Semantic web standards

ASJC Scopus subject areas

Computer Science(all)

Cite this

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AB - The large amount of patient data amassed in the Electronic Patient Record systems are of great value for medical research. Aggregating research-grade data from these systems is a laborious, often manual process. We present a semantic framework that incorporates a data semantic model and validation rules to accelerate the cleansing process for data in Electronic Patient Record systems. We demonstrate the advantages of this semantic approach in assuring data quality over traditional data analysis methods.

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KW - Data quality measurement

KW - Ontology modelling

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KW - Semantic web standards

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A semantic framework for data quality assurance in medical research

Abstract

Keywords

ASJC Scopus subject areas

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