Terminology and Ontology Development for Semantic Annotation: A Use Case on Sepsis and Adverse Events

Tracking #: 3118-4332

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Melissa Yan
Lise Tuset Gustad
Lise Husby Høvik
Øystein Nytrø

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Guest Editors SW Meets Health Data Management 2022

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Annotations enrich text corpora and provide necessary labels for natural language processing studies. To reason and infer underlying implicit knowledge captured by labels, an ontology is needed to provide a semantically annotated corpus with structured domain knowledge. Utilizing a corpus of adverse event documents annotated for sepsis-related signs and symptoms as a use case, this paper details how a terminology and corresponding ontology were developed. The Annotated Adverse Event NOte TErminology (AAENOTE) represents annotated documents and assists annotators in annotating text. In contrast, the complementary Catheter Infection Indications Ontology (CIIO) is intended for clinician use and captures domain knowledge needed to reason and infer implicit information from data. The approach taken makes ontology development understandable and accessible to domain experts without formal ontology training. AAENOTE, CIIO, and their corresponding SPARQL queries used to answer competency questions are available at https://github.com/melissayan/aaenote_and_ciio.
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