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
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
- describes how the entities referenced by the data relate to
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
- developing methodologies for leveraging widely adopted
terminologies and concept-based ontologies through realism-based
- 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,
- developing methodologies and algorithms for automated ontology
We tailor our training in biomedical ontology to your academic
- 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