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EpiJSON: A unified data-format for epidemiology.

Thomas J R Finnie1, Andy South2, Ana Bento3

  • 1Emergency Response Department Science and Technology, Public Health England, Porton Down, Salisbury, United Kingdom.

Epidemics
|June 9, 2016
PubMed
Summary

Epidemiology faces data challenges due to varied formats. EpiJSON, a new JavaScript Object Notation format, offers a flexible, standards-compliant solution for precise and unambiguous epidemiological data transfer.

Keywords:
Communications standardsDatabasesEpidemicsOutbreaksSoftware

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Area of Science:

  • Epidemiology
  • Data Science
  • Public Health Informatics

Background:

  • Divergent data recording and transfer methods complicate epidemiological analysis.
  • Expanding data types exacerbate challenges in data fidelity and interoperability.
  • A need exists for a consistent, interpretable, and precise epidemiological data transfer standard.

Purpose of the Study:

  • Introduce EpiJSON, a novel, flexible, and standards-compliant format for epidemiological data interchange.
  • Enable unambiguous storage and transfer of diverse epidemiological data across individuals, software, and institutions.
  • Provide a schema for automatic data validation and a basis for tool development.

Main Methods:

  • Developed EpiJSON based on JavaScript Object Notation and modern internet data interchange standards.
  • Created a formal schema for validating EpiJSON data.
  • Developed the R package 'repijson' for data conversion and integration with existing tools.

Main Results:

  • EpiJSON provides a flexible and unambiguous format for epidemiological data.
  • The associated schema allows for automatic data validity checks.
  • The 'repijson' package facilitates conversion between EpiJSON, line-list data, and analysis tools.

Conclusions:

  • EpiJSON offers a simple, implementable, readable, and checkable standard for epidemiological data transfer.
  • It is well-suited for the rapidly growing open-source platforms for disease outbreak analysis.
  • EpiJSON addresses the need for consistent data handling in epidemiology.