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Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques
- Source :
- JMIR Mental Health
- Publication Year :
- 2019
- Publisher :
- arXiv, 2019.
-
Abstract
- Background: Adverse Childhood Experiences (ACEs), a set of negative events and processes that a person might encounter during childhood and adolescence, have been proven to be linked to increased risks of a multitude of negative health outcomes and conditions when children reach adulthood and beyond. Objective: To better understand the relationship between ACEs and their relevant risk factors with associated health outcomes and to eventually design and implement preventive interventions, access to an integrated coherent dataset is needed. Therefore, we implemented a formal ontology as a resource to allow the mental health community to facilitate data integration and knowledge modeling and to improve ACEs surveillance and research. Methods: We use advanced knowledge representation and Semantic Web tools and techniques to implement the ontology. The current implementation of the ontology is expressed in the description logic ALCRIQ(D), a sublogic of Web Ontology Language (OWL 2). Results: The ACEs Ontology has been implemented and made available to the mental health community and the public via the BioPortal repository. Moreover, multiple use-case scenarios have been introduced to showcase and evaluate the usability of the ontology in action. The ontology was created to be used by major actors in the ACEs community with different applications, from the diagnosis of individuals and predicting potential negative outcomes that they might encounter to the prevention of ACEs in a population and designing interventions and policies. Conclusions: The ACEs Ontology provides a uniform and reusable semantic network and an integrated knowledge structure for mental health practitioners and researchers to improve ACEs surveillance and evaluation.<br />Comment: 11 Pages, 10 figures
- Subjects :
- FOS: Computer and information sciences
Knowledge management
020205 medical informatics
Knowledge representation and reasoning
Computer Science - Artificial Intelligence
Computer science
Population
02 engineering and technology
Ontology (information science)
mental health surveillance
Computer Science - Computers and Society
03 medical and health sciences
Knowledge modeling
0302 clinical medicine
Description logic
Computers and Society (cs.CY)
0202 electrical engineering, electronic engineering, information engineering
ontologies
030212 general & internal medicine
education
semantics
Semantic Web
computer.programming_language
Original Paper
education.field_of_study
computational psychiatry
business.industry
Web Ontology Language
Psychiatry and Mental health
Formal ontology
Artificial Intelligence (cs.AI)
adverse childhood experiences
business
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- JMIR Mental Health
- Accession number :
- edsair.doi.dedup.....50d0c2ede62db1f704daeae5d1453b83
- Full Text :
- https://doi.org/10.48550/arxiv.1912.05530