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KMID : 0881720200350060607
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Journal of Food Hygiene and Safety
2020 Volume.35 No. 6 p.607 ~ p.617
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Knowledge Modeling and Database Construction for Human Biomonitoring Data
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Lee Jang-Woo
Yang Se-Hee
Lee Hun-Joo
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Abstract
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Human bio-monitoring (HBM) data is a very important resource for tracking total exposure andconcentrations of a parent chemical or its metabolites in human biomarkers. However, until now, it was difficult to executethe integration of different types of HBM data due to incompatibility problems caused by gaps in study design, chemicaldescription and coding system between different sources in Korea. In this study, we presented a standardized code systemand HBM knowledge model (KM) based on relational database modeling methodology. For this purpose, we used 11 rawdatasets collected from the Ministry of Food and Drug Safety (MFDS) between 2006 and 2018. We then constructed theHBM database (DB) using a total of 205,491 concentration-related data points for 18,870 participants and 86 chemicals. Inaddition, we developed a summary report-type statistical analysis program to verify the inputted HBM datasets. This studywill contribute to promoting the sustainable creation and versatile utilization of big-data for HBM results at the MFDS.
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KEYWORD
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Human biomonitoring, Knowledge model, Database, Statistical analysis
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