Developing VISO: Vaccine Information Statement Ontology for patient education

Muhammad Amith, Yang Gong, Rachel Cunningham, Julie Boom, Cui Tao

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

Objective: To construct a comprehensive vaccine information ontology that can support personal health information applications using patient-consumer lexicon, and lead to outcomes that can improve patient education. Methods: The authors composed the Vaccine Information Statement Ontology (VISO) using the web ontology language (OWL). We started with 6 Vaccine Information Statement (VIS) documents collected from the Centers for Disease Control and Prevention (CDC) website. Important and relevant selections from the documents were recorded, and knowledge triples were derived. Based on the collection of knowledge triples, the meta-level formalization of the vaccine information domain was developed. Relevant instances and their relationships were created to represent vaccine domain knowledge Results: The initial iteration of the VISO was realized, based on the 6 Vaccine Information Statements and coded into OWL2 with Protégé. The ontology consisted of 132 concepts (classes and subclasses) with 33 types of relationships between the concepts. The total number of instances from classes totaled at 460, along with 429 knowledge triples in total. Semiotic-based metric scoring was applied to evaluate quality of the ontology.

Original languageEnglish (US)
Article number23
JournalJournal of Biomedical Semantics
Volume6
Issue number1
DOIs
StatePublished - May 1 2015
Externally publishedYes

Keywords

  • Biomedical informatics
  • Knowledge based systems
  • Ontology
  • Ontology construction
  • Vaccine Information Statements
  • Vaccines

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications
  • Health Informatics

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