Professors: Deborah L. McGuinness
Topics: Artificial Intelligence, Computer Science, Ontology, Knowledge Graph
Course Numbers: 58408; CSCI-4340-01 & 58409; CSCI-6340-01
Guest Lecturer: Ms. Elisa Kendall - ekendall at thematix dot com
Course Managers: Jade Franklin
Meeting times: Monday afternoon 12:00 pm - 3:50 pm
Location: 1140 Winslow Hall
Office Hours: TBD
Phone: 518-276-4404
Description:
This course provides an introduction to ontologies, their uses, and an overview of their application in knowledge graphs and semantically enabled systems. Ontologies encode term meanings. Ontologies, with their declarative encodings of meaning, can be used to improve communications between people and enable computer programs to function more effectively. They provide the foundation for clear and unambiguous interaction. Ontologies have become increasingly common on the web, and class participants will not only learn about the use of ontologies in web-based applications, but how to evaluate ontologies for reuse in such applications. Participants will read relevant papers, learn how to critically review ontology papers, as well as ontologies themselves, and will participate in at least one group project, designing, using, and evaluating ontologies.
To learn how to build computer understandable definitions of terms for usage in automated systems.
Goal:
To learn how to build computer understandable definitions of terms for usage in automated systems.
Learning Objective:
- Learn what ontologies are, how to build them, and how to use them
- Learn what use cases are, how to construct them, and how to use them to capture requirements for ontology and applications development
- Learn about terminology work, including definition development, and how to use terminologies as the starting point for ontology development
- Learn about ontology languages and some existing ontology resources
- Learn how to design, implement, and evaluate an ontology project
Prerequisites:
- Basic knowledge of XML is expected
- Basic knowledge of Artificial Intelligence and the Web is expected
- CSCI 2300 Data Structures and Algorithms
Note - If you are taking the class without the prerequisites, please read at least the first half of the Ontology Engineering Book and the first 5 chapters of Semantic Web for the Working Ontologist.
Assessment Criteria:
- Via written assignments
- Via oral (individual and group presentations)
- Via participation in class
- Via group evaluation
Late submission policy: first time with valid reason – no penalty, otherwise 20% of score deducted each late day.
Attendance:
Attendance at all classes is expected. If you are sick and can not attend, please contact the professors in advance. The class includes many group participation activities and participation in class is included in the final grade evaluation. Missed classes are recorded and will impact grades.
Academic Integrity:
The Rensselaer Handbook of Student Rights and Responsibilities and The Rensselaer Graduate Student Supplement define various forms of Academic Dishonesty and procedures for responding to them. All forms are violations of the trust between students and teachers. Student-teacher relationships are built on trust. For example, students must trust that teachers have made appropriate decisions about the structure and content of the courses they teach, and teachers must trust that the assignments that students turn in are their own performance. Acts that violate this trust undermine the educational process.
The Rensselaer Handbook of Student Rights and Responsibilities and The Rensselaer Graduate Student Supplement define various forms of Academic Dishonesty and you should make yourself familiar with these. In this class, all assignments that are turned in for a grade must represent the student’s own work. In cases where help was received, or teamwork was allowed, a notation on the assignment should indicate your collaboration. Submission of any assignment that is in violation of this policy will result in a penalty. If found in violation of the academic honesty policy, students may be subject to two types of penalty. The instructor administers an academic [grade] penalty and the student is reported to the Dean of Students or the Dean of Graduate Education as appropriate. The first violation results in 0 grade for that assignment. The second violation results in failure of the course. If you have any questions concerning this policy before submitting an assignment, please ask for clarification.
Students with Disabilities:
Rensselaer Polytechnic Institute strives to make all learning experiences as accessible as possible. If you anticipate or experience academic barriers based on a disability, please let the instructors know immediately so that we can discuss your options. To establish reasonable accommodations, please register with The Office of Disability Services for Students. After registration, make arrangements with us as soon as possible to discuss your accommodations so that they may be implemented in a timely fashion. DSS contact information: dss@rpi.edu; 518-276-819; 4226 Academy Hall.
Additional Information:
GitHub course page and the overall GitHub repository page
The GitHub course page has a left hand navigation bar that points to the main student projects:
Fit Me!
Personalized Depression Treatment Ontology
Political Journalism
When to Go Where
Course: Ontology Engineering
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