TY - JOUR
T1 - Developing VISO
T2 - Vaccine Information Statement Ontology for patient education
AU - Amith, Muhammad
AU - Gong, Yang
AU - Cunningham, Rachel
AU - Boom, Julie
AU - Tao, Cui
N1 - Funding Information:
This project is partially supported by the National Library Of Medicine of the National Institutes of Health under Award Number R01LM011829.
Publisher Copyright:
© 2015 Amith et al.; licensee BioMed Central.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - 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.
AB - 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.
KW - Biomedical informatics
KW - Knowledge based systems
KW - Ontology
KW - Ontology construction
KW - Vaccine Information Statements
KW - Vaccines
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U2 - 10.1186/s13326-015-0016-2
DO - 10.1186/s13326-015-0016-2
M3 - Article
AN - SCOPUS:84938775093
SN - 2041-1480
VL - 6
JO - Journal of Biomedical Semantics
JF - Journal of Biomedical Semantics
IS - 1
M1 - 23
ER -