Abstract
Background: Ontologies are key enabling technologies for the Semantic Web. The Web Ontology Language (OWL) is a semantic markup language for publishing and sharing ontologies.
Objectives: The supply of customizable, computable, and formally represented molecular genetics information and health information, via electronic health record (EHR) interfaces, can play a critical role in achieving precision medicine. In this study, we used cystic fibrosis as an example to build OntoKBCF, an ontology-based knowledge base prototype, to supply such information via an EHR prototype. In this paper, we elaborate on the construction and representation principles, approaches, applications, and representation challenges that we faced in the construction of OntoKBCF. The principles and approaches can be referenced and applied in constructing other ontology-based domain knowledge bases.
Methods: We defined the scope of OntoKBCF first according to possible clinical information needs about cystic fibrosis on both a molecular level and a clinical phenotype level. We then selected the knowledge sources to be represented in OntoKBCF. We utilized top-to-bottom content analysis and bottom-up construction to build OntoKBCF. Protégé-OWL was used to construct OntoKBCF. The construction principles included: to use existing basic terms as much as possible; to use intersection and combination in representations; to represent as
many different types of facts as possible; and to provide two to five examples for each type. HermiT 1.3.8.413 within Protégé-5.1.0 was used to check the consistency of OntoKBCF.
Results: OntoKBCF was constructed successfully, with the inclusion of 408 classes, 35 properties, and 113 equivalent classes. OntoKBCF includes both atomic concepts, such as amino acid, and complex concepts, such as
adolescent female cystic fibrosis patients, and their descriptions. We demonstrated that OntoKBCF could make customizable molecular and health information available automatically and usable via an EHR prototype. The
main challenges include the provision of a more comprehensive account of different patient groups and the representation of uncertain knowledge, ambiguous concepts, and negative statements, and more complicated and
detailed molecular mechanisms or pathway information about cystic fibrosis.
Conclusions: Although cystic fibrosis is just one example, based on the current structure of OntoKBCF, it should be relatively straightforward to extend it to cover different topic areas. Moreover, the principles underpinning its
development could be reused for building alternative human monogenetic diseases knowledge bases
Objectives: The supply of customizable, computable, and formally represented molecular genetics information and health information, via electronic health record (EHR) interfaces, can play a critical role in achieving precision medicine. In this study, we used cystic fibrosis as an example to build OntoKBCF, an ontology-based knowledge base prototype, to supply such information via an EHR prototype. In this paper, we elaborate on the construction and representation principles, approaches, applications, and representation challenges that we faced in the construction of OntoKBCF. The principles and approaches can be referenced and applied in constructing other ontology-based domain knowledge bases.
Methods: We defined the scope of OntoKBCF first according to possible clinical information needs about cystic fibrosis on both a molecular level and a clinical phenotype level. We then selected the knowledge sources to be represented in OntoKBCF. We utilized top-to-bottom content analysis and bottom-up construction to build OntoKBCF. Protégé-OWL was used to construct OntoKBCF. The construction principles included: to use existing basic terms as much as possible; to use intersection and combination in representations; to represent as
many different types of facts as possible; and to provide two to five examples for each type. HermiT 1.3.8.413 within Protégé-5.1.0 was used to check the consistency of OntoKBCF.
Results: OntoKBCF was constructed successfully, with the inclusion of 408 classes, 35 properties, and 113 equivalent classes. OntoKBCF includes both atomic concepts, such as amino acid, and complex concepts, such as
adolescent female cystic fibrosis patients, and their descriptions. We demonstrated that OntoKBCF could make customizable molecular and health information available automatically and usable via an EHR prototype. The
main challenges include the provision of a more comprehensive account of different patient groups and the representation of uncertain knowledge, ambiguous concepts, and negative statements, and more complicated and
detailed molecular mechanisms or pathway information about cystic fibrosis.
Conclusions: Although cystic fibrosis is just one example, based on the current structure of OntoKBCF, it should be relatively straightforward to extend it to cover different topic areas. Moreover, the principles underpinning its
development could be reused for building alternative human monogenetic diseases knowledge bases
Original language | English |
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Article number | e52 |
Number of pages | 15 |
Journal | JMIR Medical Informatics |
Volume | 6 |
Issue number | 4 |
DOIs | |
Publication status | Published - 21 Dec 2018 |