Course Syllabus


This is course is organized into four modules (each of which is at least 2 weeks long): 

  1. Describing data, storing data, sharing data. Linked Open Data, RDF and URIs.
  2. Ontologies and querying the semantic web via SPARQL. 
  3. The theory underlying reasoning and inference for knowledge representation. In practice, we will use two specific sorts of reasoning systems: rule-based systems and description-logic reasoning in OWL.
  4. Machine learning, big data, and methods for probabilistic and uncertain knowledge representation.

Each of the first three modules culminates in a hands-on project. For the final module, you must carry out a summative final project, which covers ideas and topics from the entire course. Except for the first project, you will work in teams on these projects. 


Your grade will be primarily based on your performance on the four projects as follows: Proj1: 15%, Proj2: 20%, Proj3: 25%, Proj4: 25%. Note that some of these projects will be carried out in teams. The final 15% of your grade will depend on classroom participation and discussion board postings. The project descriptions include grading rubrics. Usually, all team members will receive the same grade for projects (but not in all cases).  I will strive to explain my grading, and I will certainly make myself available via appointment or office hours for discussion, but caveat emptor, all grading is subjective.  During the first week of class, I will aim to describe my philosophy about grading; see also Amy Ko's blog post on the subject. 

Week-by-week course schedule


Required Course Textbook

Semantic Web for the Working Ontologist, (second edition) by Allemang and Hendler, 2011.
Available from Amazon (Links to an external site.).  Note that most reading will be made available on the Course Schedule page.

Course Summary:

Date Details Due