ArticleFrontiers in microbiology2017
Context Is Everything: Harmonization of Critical Food Microbiology Descriptors and Metadata for Improved Food Safety and Surveillance.
Article in Frontiers in microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Food-borne bacterial pathogens: emerging approaches in detection and prevention.Archives of microbiology · 2026Review
- Genomic diversity and antimicrobial resistance ofMicrobial genomics · 2025Article
- Hygienic practices and associated factors in slaughterhouses and meat retail shops in Hawasa City, Ethiopia.PloS one · 2025Article
- Next generation biobanking ontology: introducing-omics contextual data to biobanking ontology.Bioinformatics advances · 2025Article
- Antimicrobial Resistance Surveillance: Data Harmonisation and Data Selection within Secondary Data Use.Antibiotics (Basel, Switzerland) · 2024Article
- Metadata harmonization-Standards are the key for a better usage of omics data for integrative microbiome analysis.Environmental microbiome · 2022Article
- Multidrug Resistance Dynamics in Salmonella in Food Animals in the United States: An Analysis of Genomes from Public Databases.Microbiology spectrum · 2021Article
- Antibiotic Resistance: One Health One World Outlook.Frontiers in cellular and infection microbiology · 2021Review
- Quantifying the transmission of antimicrobial resistance at the human and livestock interface with genomics.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2020Review
- Performance and Accuracy of Four Open-Source Tools forApplied and environmental microbiology · 2020Article
- Whole genome sequencing and metagenomics for outbreak investigation, source attribution and risk assessment of food-borne microorganisms.EFSA journal. European Food Safety Authority · 2019Article
- A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology: GEViT.Bioinformatics (Oxford, England) · 2019Article
- Human Disease Ontology 2018 update: classification, content and workflow expansion.Nucleic acids research · 2019Article
- Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges.Frontiers in microbiology · 2019Review
- Spfy: an integrated graph database for real-time prediction of bacterial phenotypes and downstream comparative analyses.Database : the journal of biological databases and curation · 2018Article
- FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration.NPJ science of food · 2018Article
- Interpreting Whole-Genome Sequence Analyses of Foodborne Bacteria for Regulatory Applications and Outbreak Investigations.Frontiers in microbiology · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Globalization of food networks increases opportunities for the spread of foodborne pathogens beyond borders and jurisdictions. High resolution whole-genome sequencing (WGS) subtyping of pathogens promises to vastly improve our ability to track and control foodborne disease, but to do so it must be combined with epidemiological, clinical, laboratory and other health care data (called "contextual data") to be meaningfully interpreted for regulatory and health interventions, outbreak investigation, and risk assessment. However, current multi-jurisdictional pathogen surveillance and investigation efforts are complicated by time-consuming data re-entry, curation and integration of contextual information owing to a lack of interoperable standards and inconsistent reporting. A solution to these challenges is the use of 'ontologies' - hierarchies of well-defined and standardized vocabularies interconnected by logical relationships. Terms are specified by universal IDs enabling integration into highly regulated areas and multi-sector sharing (e.g., food and water microbiology with the veterinary sector). Institution-specific terms can be mapped to a given standard at different levels of granularity, maximizing comparability of contextual information according to jurisdictional policies. Fit-for-purpose ontologies provide contextual information with the auditability required for food safety laboratory accreditation. Our research efforts include the development of a Genomic Epidemiology Ontology (GenEpiO), and Food Ontology (FoodOn) that harmonize important laboratory, clinical and epidemiological data fields, as well as existing food resources. These efforts are supported by a global consortium of researchers and stakeholders worldwide. Since foodborne diseases do not respect international borders, uptake of such vocabularies will be crucial for multi-jurisdictional interpretation of WGS results and data sharing.
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