Description
HemOnc.org is a large collaborative wiki providing evidence-based information on cancer regimens, along with their indications, components, and supporting literature. This project evaluates candidate data representation models for HemOnc.org content. Wiki content was obtained via a web-scraping algorithm. The resultant data was transformed into an OWL ontology, and it was subsequently converted to a custom relational database, a Neo4j graph database, and an OHDSI concept-relationship data model. We will compare and contrast these different formats.
Learning Objective: Understand the role of HemOnc.org in the oncology and informatics communities.
Understand the process of extracting information from a wiki into information models.
Be able to compare and contrast ontology models, graph databases, and relational databases for appropriateness with HemOnc.org data.
Authors:
Zachary Moldwin (Presenter)
UIC College of Pharmacy
Harry Hochheiser, University Of Pittsburgh
Jeremy Warner, Vanderbilt University
Presentation Materials: