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A Schema for Digitized Surface Swab Site Metadata in Open-Source DNA Sequence Databases.

Jingzhang Feng¹, Devin Daeschel¹, Damion Dooley²

¹Department of Food Science, Cornell University, Ithaca, New York, USA.

|February 27, 2023

Summary

Standardizing swab site metadata in pathogen surveillance improves data quality. This enables better analysis of DNA sequence databases for public health and food safety applications.

Keywords:

epidemiology foodborne pathogen genomic surveillance informatics

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Area of Science:

Microbiology and Bioinformatics
Genomic Epidemiology
Public Health Surveillance

Background:

Large-scale DNA sequence databases are crucial for public health surveillance of microbial pathogens.
Current metadata collection for swab site locations is unstructured, leading to poor data quality and hindering automated analysis.
Inconsistent free-text descriptions in the 'isolation source' field impede machine-actionability and data interoperability.

Purpose of the Study:

To develop a standardized, hierarchical vocabulary for describing microbial pathogen swab site locations.
To improve the machine-actionability and quality of metadata in public DNA sequence databases.
To enhance the utility of genomic data for public health surveillance and food safety.

Main Methods:

Content analysis of 1,498 free-text swab site descriptions from foodborne pathogen surveillance.
Evaluation of metadata lexicon to identify informational facets and unique terms.
Development of hierarchical vocabularies and logical relationships using Open Biological Ontologies (OBO) Foundry libraries.

Main Results:

Identified 5 key informational facets and 338 unique terms within the free-text metadata.
Developed a structured schema with hierarchical vocabularies and logical axioms for swab site locations.
Integrated the developed schema into a publicly available pathogen metadata standard (One Health Enteric Package).

Conclusions:

Standardized metadata, particularly for swab site locations, is essential for improving the quality and interoperability of DNA sequence databases.
The developed vocabulary system facilitates large-scale data sharing, artificial intelligence, and big-data solutions for food safety.
Implementation of metadata standards supports the future of open genomic epidemiology networks and efficient public health investigations.