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An Ontological Representation for the Real-Time Evaluation of Vaccine Coverage, Safety, and Effectiveness
- Publication Year :
- 2023
-
Abstract
- Data used when studying vaccination programs and vaccine evaluations are collectedfrom multiple, and constantly changing data sources. These data sources are often isolateddata silos, that are hard for researchers and public health organizations to connect, andthus hinders when researchers and public health organizations are conducting these studies. A solution for this hindrance are well-designed ontologies. Ontologies are becomingincreasingly relevant with the massive increase of data online. Equally relevant is handling ontologies according to the FAIR principles, since it is considered the best practicesof handling scientific data. This thesis presents a design process for modeling an ontology in order to representvaccine coverage, safety and adverse events, and vaccine effectiveness for real-time evaluation when existing ontologies are taken into consideration. The design process was inspired by the METHONTOLOGY method and the XD method. The scope was specified viathree stories each representing one aspect (vaccine coverage, safety and adverse events,and vaccine effectiveness), and relevant terms were gathered via knowledge acquisition.They were both validated by a domain expert before integration and implementation ofeach story, forming a module, were performed. In the integration and implementation,noticeable impact of the FAIR principles was seen since FAIRsFAIR’s 17 recommendationswere followed. The impact of the guidelines suggested foundational ontologies and reuseof ontologies which also follow the FAIR principles should be used to the extent possible.This thesis also presents how the modeled ontology could be evaluated by three aspects:internal evaluation, external evaluation, and FAIRness. Both the internal and external evaluation regarded the quality criterion accuracy and coverage. The internal evaluation included verification of requirements, also the coverage, and predicting the accuracy by semantic variance. The external evaluation was conducted b
Details
- Database :
- OAIster
- Notes :
- application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1372274794
- Document Type :
- Electronic Resource