Implementing a New FHIR RDF Specification for Semantic Clinical Data Using a JSONLD- based Approach

Deepak K. Sharma, Eric Prud'Hommeaux, David Booth, Kevin J. Peterson, Daniel J. Stone, Harold Solbrig, Guohui Xiao, Emily Pfaff, Guoqian Jiang

Research output: Contribution to journalConference articlepeer-review

Abstract

FHIR RDF enables operational healthcare data to be linked with RDF data from other communities. FHIR data can be serialized in either JSON, XML or RDF (Turtle), and tools are used to convert between formats. However, currently the tools for converting to/from FHIR RDF involve custom code. JSON-LD 1.1 @context files now have potential to reduce the cost of implementing and maintaining this FHIR RDF conversion. These @context files can be generated automatically during the FHIR specification build process. Used with a standard, off-the-shelf JSON-LD 1.1 processor, these @context files can do most of the work needed for this conversion, though a small amount of pre- or post-processing is still needed. Using the latest FHIR build and server implementations, we created a framework for the FHIR RDF specification implementation by developing two tools to demonstrate this process: a JSON-LD 1.1 @context generator that produces @context files from the FHIR specification; and a command-line tool for batch conversion between FHIR JSON and FHIR RDF.

Original languageEnglish (US)
Pages (from-to)82-86
Number of pages5
JournalCEUR Workshop Proceedings
Volume3127
StatePublished - 2022
Event13th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences, SWAT4HCLS 2022 - Virtual, Leiden, Netherlands
Duration: Jan 10 2022Jan 14 2022

Keywords

  • Healthcare
  • HL7 FHIR
  • JSON-LD
  • JSON-LD Context
  • RDF
  • Shape Expression
  • ShEx

ASJC Scopus subject areas

  • Computer Science(all)

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