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Research Areas

NCOR supports research across a range of areas in ontology, including:

  • Foundational ontology development
  • Domain ontology implementation
  • Cross-cultural ontology integration
  • Ontology for artificial intelligence

NCOR researchers work across multiple dimensions of ontology theory and practice. Our research explores both foundational questions and practical applications across disciplines, building bridges between philosophical inquiry and real-world implementation.

NCOR's research initiatives have demonstrable impact across multiple domains:

  • Standards Development: Contributing to ISO/IEC standard 21838 (Basic Formal Ontology)
  • Open Science: Advancing reproducible research through ontology-based data annotation
  • Artificial Intelligence: Developing ontological foundations for explainable AI
  • Healthcare: Improving data integration for clinical care and biomedical research
  • Defense & Security: Enhancing intelligence gathering and analysis through ontology-based approaches
  • Cross-Domain Applications: Supporting semantic interoperability across diverse knowledge domains

Our interdisciplinary approach brings together philosophical rigor, logical formalism, and practical implementation to address complex information management challenges in both academic and industrial settings.

Foundational Ontology​

Foundational (or top-level) ontologies provide the basic categories and relations needed to describe reality across all domains of knowledge. This research area focuses on developing and refining overarching frameworks that can be used to organize more specialized ontologies in a consistent and coherent manner.

At NCOR, we are particularly known for our work on Basic Formal Ontology (BFO), which has been adopted as ISO/IEC standard 21838 and serves as a starting point for hundreds of domain ontologies worldwide. Our research examines fundamental ontological distinctions such as:

  • Continuants vs. occurrents
  • Independent vs. dependent entities
  • Material vs. immaterial entities
  • The nature of qualities, relations, and processes

This work provides the theoretical grounding necessary for building interoperable information systems and knowledge bases that accurately represent both physical and abstract aspects of reality.

Biomedical Ontologies​

The biomedical domain represents one of the most successful applications of ontological methods, with projects like the Gene Ontology revolutionizing how researchers annotate and integrate biological data.

NCOR's biomedical ontology research encompasses:

  • Development of reference ontologies for biological domains
  • Integration of clinical and research data through ontology-based methods
  • Representation of disease processes, anatomical structures, and biological functions
  • Frameworks for describing biomedical investigations and their results

Biomedical ontology work has practical applications in precision medicine, drug discovery, electronic health records, and public health surveillance systems. By providing standardized vocabularies and data models, these ontologies enable unprecedented integration of biomedical knowledge across species, scales, and specialties.

Community development of interoperable ontologies for the biomedical domain is done under the auspices of the OBO Foundry.

Semantic Interoperability​

As information systems multiply, the need to exchange data meaningfully between different platforms becomes increasingly critical. Semantic interoperability research addresses how systems can not only exchange data but preserve its meaning across contexts.

This research area explores:

  • Methods for aligning and mapping between different ontologies
  • Techniques for ontology-based data integration
  • Standards and protocols for semantic data exchange
  • Cross-domain and cross-cultural concept representation

Our work in semantic interoperability has applications in healthcare information exchange, intelligence community data sharing, enterprise knowledge management, and international standards development. By developing principled approaches to meaning preservation across systems, we help solve some of the most challenging data integration problems facing organizations today.

Ontology Methodology​

Creating effective ontologies requires sound methodological principles. This research area develops and refines the theoretical foundations and practical techniques of ontology development.

Key aspects of our methodology research include:

  • Principles for ontology design and evaluation
  • Methods for capturing domain knowledge from experts
  • Approaches to ontology modularization and reuse
  • Balancing expressivity with computational efficiency

By advancing methodological knowledge, we help organizations develop ontologies that are logically coherent, domain-appropriate, and practically useful. Our research distinguishes between good and poor ontological choices, guiding practitioners toward solutions that will stand the test of time.

Ontology Engineering​

While methodology focuses on principles, ontology engineering addresses the practical tools and techniques needed to build, maintain, and evolve ontologies throughout their lifecycle.

This research area encompasses:

  • Development and evaluation of ontology editing tools
  • Methods for ontology versioning and change management
  • Techniques for automated reasoning with ontologies
  • Approaches to collaborative ontology development

Our engineering research helps bridge the gap between theoretical ontology and practical implementation, ensuring that the benefits of ontological analysis can be realized in real-world systems. We work with software developers, domain experts, and end users to create ontology engineering solutions that meet practical needs while maintaining philosophical rigor.

Industrial Ontologies​

Industrial ontologies play a crucial role in optimizing processes across various sectors, including manufacturing, supply chain management, and product lifecycle management. This research area focuses on developing ontologies that facilitate efficient operations, enhance interoperability, and support decision-making in industrial contexts.

Key topics in our industrial ontology research include:

  • Ontological frameworks for modeling manufacturing processes and workflows
  • Integration of supply chain data through standardized ontological representations
  • Lifecycle management of products using ontology-driven approaches
  • Methods for ensuring data consistency and interoperability across industrial systems

By leveraging industrial ontologies, we empower organizations to streamline operations, improve collaboration, and drive innovation. Our work emphasizes practical applications that align with industry needs while maintaining a robust theoretical foundation, distinguishing NCOR's approach as both practical and philosophically sound.