iOntoBioethics

iOntoBioethics constructs and validates bioethics ontologies to represent and analyze ethical concepts and relationships relevant to pandemics such as COVID-19.

Key Features:

• Agile ontology development: Two-stage process combining manual curation (Manually Constructing Bioethics - MCB) and automated ontology generation under an agile approach grounded in Design Science Research Methodology.
• Extensive literature base: Systematic mapping of 26,170 Scopus-indexed bioethics articles published since 1971 to source ontology concepts.
• Automated text mining and machine learning: Uses advanced Text Mining and Machine-Learning techniques, including automated topic modeling, for ontology generation.
• Comprehensive ontological models: Integrates approximately 700 concepts and associations, including COVID-19–specific concepts, organized into high-level abstractions and a structured hierarchy.
• Validation by experts: Both manually constructed and machine-generated ontologies are validated by domain experts.
• Dynamic enrichment and updates: Supports regular updates and semi-automatic enrichment to incorporate new bioethics insights during ongoing pandemics.

Scientific Applications:

• Governance of bioethics processes: Links bioethical concepts with healthcare system processes to support automated governance and decision-making in pandemic contexts.
• Bioethics informatics foundation: Provides a foundational ontology to enable computational analysis and knowledge integration in the field of Bioethics Informatics.
• Big data analytics platform: Serves as a knowledge backbone for analytics that monitor governance adherence and integrate emerging bioethics knowledge in pandemic responses.

Methodology:

Systematic literature mapping of Scopus articles, manual ontology construction (MCB), followed by automated topic modeling and ontology generation using a specialized Text Mining and Machine-Learning engine, with semi-automatic enrichment.