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Samadian, Soroush; McManus, Bruce M.; Wilkinson, Mark

BioMed Central

Background: Measurement-unit conflicts are a perennial problem in integrative research domains such as clinical meta-analysis. As multi-national collaborations grow, as new measurement instruments appear, and as Linked Open Data infrastructures become increasingly pervasive, the number of such conflicts will similarly increase. Methods: We propose a generic approach to the problem of (a) encoding measurement units in datasets in a machine-readable manner, (b) detecting when a dataset contained mixtures of measurement units, and (c) automatically converting any conflicting units into a desired unit, as defined for a given study. Results: We utilized existing ontologies and standards for scientific data representation, measurement unit definition, and data manipulation to build a simple and flexible Semantic Web Service-based approach to measurement-unit harmonization. A cardiovascular patient cohort in which clinical measurements were recorded in a number of different units (e.g., mmHg and cmHg for blood pressure) was automatically classified into a number of clinical phenotypes, semantically defined using different measurement units. Conclusions: We demonstrate that through a combination of semantic standards and frameworks, unit integration problems can be automatically detected and resolved.

Text

2016-01-13

Attribution 4.0 International (CC BY 4.0)

http://hdl.handle.net/2429/56482

BMC Medical Genomics. 2014 May 08;7(Suppl 1):S12

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Samadian et al.; licensee BioMed Central Ltd.

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