Semantic Web Topics (Fall 2016)

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  • Prepare students for research in semantic technologies
  • Teach students how to
    • Read papers,
    • Present research ideas,
    • Synthesize material,
    • Critically review (as one might do for a publication venue)
  • Teach students how to develop a literature corpus for use in research
This course will discuss emerging trends in semantics research, focusing on knowledge representation, management, and modeling, including applications of knowledge graphs and ontologies. This is a seminar course, not a lecture course. We will have many presentations and discussions throughout the course that help you to understand, conduct, and evaluate academic research while we discuss the emerging trends in semantic technologies. This course is intended to allow students to produce a research survey that can fulfill their research qualifying examination. 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 knowledge representation systems.
  • Prepare students for research in semantic technologies
  • Teach students how to
    • Read papers,
    • Present research ideas,
    • Synthesize material,
    • Critically review (as one might do for a publication venue)
  • Teach students how to develop a literature corpus for use in research
Learning Objective:
  • Learn to critically review semantic technology papers
  • Learn to create & deliver technical presentations on research: individually & in groups*
  • Learn to prepare AND evaluate a research paper review
  • Learn to prepare research papers about a specific semantic web research question
  • Learn to create a related work corpus and annotated bibliography
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
  • Most assignments will be due midnight ET Thursday (but check each assignment carefully)
Academic Integrity:
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. Acts, which violate this trust, undermine the educational process. The Rensselaer Handbook of Student Rights and Responsibilities defines 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 dishonesty policy, students may be subject to two types of penalties. The instructor administers an academic (grade) penalty, and the student may also enter the Institute judicial process and be subject to such additional sanctions as: warning, probation, suspension, expulsion, and alternative actions as defined in the current Handbook of Student Rights and Responsibilities. If you have any question concerning this policy before submitting an assignment, please ask for clarification.

Course Syllabus

See the google docs page:

NOTICE: remember to check back as the schedule may change as the term progresses.

Course Calendar

Refer to Reading / Assignment / Reference list for each week (see below). Note that the schedule and the reading list may evolve as the class progresses. Also some related class web pages from Tetherless World professors may be of use for additional readings from []

For each week, two students will present papers on the scheduled topic. Two papers will be assigned to the entire class, and each student will present an additional paper that they select from the broader literature. All assignments are due at midnight ET the Thursday before the class.

Note the topics and their order may change

  • CLASS 1: Monday, August 29 - Introduction to the course and literature review (slides)
  • NO CLASS on Labor Day September 5
  • CLASS 2: Monday, September 12 - Knowledge Graphs
  • CLASS 3: Monday September 19 - Use Cases for Semantic Technology Applications
  • CLASS 4: Monday, September 26 - Research survey topic presentations (10 minutes plus discussion) or Semantic Workflows (Tentative)
  • CLASS 5: Monday, October 3 - Scientific knowledge representation
  • Columbus Day October 10
  • CLASS 6: TUESDAY, October 11 - Nanopublications
  • CLASS 7: Monday, October 17 - Social graphs
  • CLASS 8: Monday, October 24 * - Semantic Analytics
  • CLASS 9: Monday October 31 - Collaborative Ontologies
  • CLASS 10: Monday November 7 - Semantic Information Extraction
  • CLASS 11: Monday, November 14 * - Present your current research with in class critiques
  • CLASS 12: Monday, November 21 - Web Science
  • CLASS 13: Monday, November 29 - Project Presentations
  • CLASS 14: Monday, December 5 - Class Roundtable/followups (final exam week following week)

Attendance Policy

Enrolled students may miss at most one class without permission of the instructor. Once one class has been missed (with or without permission) no additional classes may be missed without permission.

Research Project

All research-related submissions must be done through easychair. Please create an account using the conference page we have set up there.

Reading List

Class 2: Knowledge Graphs (Reading from Homework Assignment 1)

  1. Gettier, E.L.: Is Justified True Belief Knowledge? Analysis 23(6), 121–123 (jun 1963).
  2. Stokman, Frans N., and Pieter H. de Vries. "Structuring knowledge in a graph." Human-Computer Interaction. Springer Berlin Heidelberg, 1988. 186-206.
  3. Singhal, A.: Introducing the knowledge graph: things, not strings. Official Google Blog, May (2012).
  4. James P. McCusker, Katherine Chastain, John S. Erickson, and Deborah L. McGuinness What is a Knowledge Graph? (unpublished).
  5. An article cited the What is a Knowledge Graph Paper above.

Class 3: Use Cases for Semantic Technologies

  1. Elisa Kendall and Deborah McGuinness. Use Cases Chapter, Ontology Engineering, Forthcoming book 2016.
  2. Rachel Davies. The Power of Stories. Proceedings Extreme Programming, Villasimius, Italy, 2001.
  3. Len Bass, John K. Bergey, Paul C. Clements, Paulo Merson, Ipek Ozkaya, Raghvinder Sangwan. A Comparison of Requirements Specification Methods from a Software Architecture Perspective. Carnegie Mellon University Software Engineering Institute CMU/SEI Report Number: CMU/SEI-2006-TR-013. August 2006.


All assignments are due Thursday at midnight before the class indicated.

Class 2: Read and review Knowledge Graph papers

Summary: Compose a paper (up to 5 pages) that reviews and evaluates the assigned papers. What are the claims of each paper? Are they justified? How are they justified? Are the claims grounded in the relevant research? Do their references support the claims that the paper attributes to them?

Class 3: Read and review the use case papers.


Class 4: Research Topic Selection

Select or create a research topic and prepare presentation of it and any preliminary research on it.

Link to assignment

Class 5: Research Topic Revision

Link to assignment

Revise survey topics based on in-class feedback, submit abstract to easychair for final approval.

Class 6: Paper Outline and References, Review Bidding

Submit your paper outline with references to Easychair. Select the papers from classmates that you are most interested in reviewing using the easychair bidding process. Bidding closes on Thursday at midnight.

Link to assignment

Class 7: Social Graphs

Link to assignment

Class 8: Paper Submission and Semantic Workflows

Submit the review-ready versions of your paper to EasyChair and readings on Semantic Workflows.

Link to assignment

Class 9: Paper reviews and Collaborative Ontologies

Link to assignment

Class 10: Paper updates and semantic information extraction / natural language

Link to assignment

Class 11: Review revisions and project presentation preparation

Link to assignment)

Class 12: Review updates based on revisions

Link to assignment

Class 13: Final revisions

Link to assignment

Class 14: Project presentations

Link to assignment

Class 15: Class Roundtable and Project updates

Link to assignment