本体支持的生物医学领域元数据异质性与可兼容性研究

doi:10.3969/j.issn.0258-8021.2019.03.009

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Abstract Using ontologies to support the representation of data elements is an important means to improve the machine′s understanding of metadata. In this paper, we evaluated the semantic heterogeneity of data elements in caDSR and assessed two related data elements integration ability. First, 60 pairs of common data elements were selected from caDSR, covering demography, lifestyle, medical history and laboratory measurements. Next, the essential components of data elements were extracted according to the ISO/IEC11179 standard and the similarity of these essential components between every pair of data elements with the support of NCIT was calculated. At last, the compatibility between related data elements was predicted by using SVM based on the semantic similarity between corresponding CDE components. The overall accuracy was above 80%. The results showed that there was currently considerable heterogeneity in the definition of metadata in the caDSR database, especially in the conceptual domain of data elements. Nevertheless, our method still could realize the automatic judgement of data compatibility based on the definition of existing data elements by the help of machine learning. The method established in this study has a certain value for optimizing data element construction process and enriching data standardization tools.

Key words： metadata heterogeneity common data element ontology supporting vector machine(SVM)

Received: 14 March 2019

PACS:

R318

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	Articles by authors
	Zhang Lulu
	Yang Sheng
	Shi Furen
	Pan Hongjie
	Wang Zhigang
	Yang Xiaolin

Cite this article:

Zhang Lulu,Yang Sheng,Shi Furen, et al. Research on Heterogeneity and Compatibility of Biomedical Field Metadata Supported by Ontology[J]. Chinese Journal of Biomedical Engineering, 2019, 38(3): 324-331.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2019.03.009 OR http://cjbme.csbme.org/EN/Y2019/V38/I3/324

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