Applied Ontology MS

UB is the world center of research and education in Applied Ontology, and the demand for UB-trained ontologists has been expanding rapidly both nationally and internationally since the turn of the millennium. This fully online Applied Ontology MS program equips students with the theoretical and technical skills needed to develop, implement, and manage ontologies for artificial intelligence, biomedical informatics, data science, knowledge engineering, and other emerging fields.

Required Courses (9 credits)

PHI 530LEC - Ontological Engineering Credits: 3
PHI 531SEM - Problems in Ontology Credits: 3
PHI 598SEM - Applied Ontology Seminar Credits: 3

Sample Electives Courses (15-18 credits)

BMI 501SEM - Survey of Biomedical Informatics Credits: 3
BMI 508SEM - Biomedical Ontology Credits: 3
CSE 560LEC - Data Models Query Lang Credits: 3
CSE 562LEC - Database Systems Credits: 3
GEO 511LEC - Spatial Data Science Credits: 3
GEO 595LEC - Database Design for GIS Credits: 3
LIN 567LEC - Computational Linguistics Credits: 3
MGS 628LEC - Data Visualization for Business Insights Credits: 3
PHI 550SEM - Spatial Ontology Credits: 3
PHI 596TUT - Applied Ontology Internship Credits: 1-3
PHI 599TUT - Graduate Tutorial Credits: 1 - 6
PHI 635LEC - Logic for Ontologies Credits: 3
PHI 650SEM - Ontology of Society Credits: 3

Thesis (3-6 credits)

PHI 701TUT - MA Thesis Guidance Credits: 1 - 6

Total Credit Hours: 30

3.0 Degree GPA required

Program Learning Outcomes (PLOs)

Develop Expertise in Ontology Engineering

Graduates will be proficient in ontology modeling, knowledge representation, and data interoperability, demonstrated by the successful completion of PHI 530: Ontology Engineering and PHI 598: Applied Ontology Seminar.
Graduates will be able to design and implement ontologies using industry-standard tools such as OWL and Protégé, with at least one portfolio project showcasing their ability to solve real-world data challenges.
Graduates will understand the place of philosophy and logic in its broader cognitive and social context.
Graduates will be master the ability to construct arguments for choosing between alternative analyses of architecture implementations and to identify relevant data bearing on such analyses.
Graduates will achieve awareness of novel and emerging strategies for leveraging artificial intelligence methods in ontology implementations

Advance Career Readiness and Professional Contributions

The program aims to have within one year of graduation at least ¾ of its graduates employed in roles involving ontology development, knowledge management, or AI-driven data solutions.
This objective is supported by the program’s online format tailored for working professionals, industry-aligned coursework, and a culminating portfolio project that demonstrates competency to potential employers.

Apply Ontological Methods to Domain-Specific Problems

Graduates will be able to analyze and address ontological challenges in their professional fields, such as AI, biomedical informatics, government, and industry.
Graduates will be assessed through successful completion of at least three elective courses focused on domain applications (e.g., healthcare, cybersecurity, business intelligence) and a directed research project where students apply ontological methods to a real-world problem in their area of expertise.
Graduates will be able to analyze a complex domain-specific modeling problem and apply principles of applied ontology and other relevant disciplines to identify solutions.
Graduates will be able to design, implement and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.

General Learning Outcome

Communicate effectively in a variety of professional, industrial and scientific contexts.

SED Statement

This new program is pending official registration with the New York State Education Department (SED).