In health care settings, information technology (IT) must provide accurate, to-the-point information to specific parties to minimize the burden of manual data input or explicit information requests.
This requires the seamless cooperation of purpose-specific, semantically interoperable IT applications and processes. They must use, or contribute to, a data pool that:
- allows each data element to identify what it describes uniquely
- describes how the entities referenced by the data relate to each other
Our division educates trainees in these realism-based ontologies — their theory, standards and development. Our studies in this field yield findings that help health care IT systems function at their peak for the distinct users they serve.
Specifically, our research involves:
- designing, implementing and applying referent tracking-compatible languages and reasoners
- extending existing — or designing new — representation languages and formal reasoners capable of exploiting the potential of realism-based ontology development, auditing and curation
- developing methodologies for leveraging widely adopted terminologies and concept-based ontologies through realism-based ontology
- designing health care information systems that can derive maximum benefits from realism-based ontologies
- self-explanatory and explicit data collection
- developing ontologies for specific applications (natural language understanding, longitudinal patient-record linking, etc.)
- developing methodologies and algorithms for automated ontology development
We tailor our training in biomedical ontology to your academic stage.
- Undergraduate students: We’ll teach you the basics of terminology and ontology for the biomedical sciences.
- Graduate students: You’ll learn the principles of realism-based ontology development.
- Medical students: Become acquainted with ontology-based research data collection and management.
- Postdoctoral scholars: Collaborate with us to develop ontology-based information systems.
We provide researchers quality control in ontology development. We also can help collect and manage data for semantic interoperability.