IST 731 Knowledge Organization Structures

Spring 2005 (tentative)

 

Instructor: Jian Qin  (4-187 CST, jqin@syr.edu)

Place and time: HL207, Tuesday 3:30-6:15

 

Description

The continuing and fast growth of digital information in volume and complexity creates unprecedented challenges to information system users and developers. Strategies for addressing these challenges require knowledge from library and information science, computer science, linguistics, psychology, and other related disciplines. This course is designed to provide knowledge and skills that are fundamental for responding to the challenges of digital information. Specifically, the course will discuss 1) knowledge modeling methods and representation of concepts and their relationships, augmented by case studies of common knowledge organization methods; 2) knowledge structures that are used in many information systems, including classifications, thesauri, lexicons, and ontologies; 3) knowledge technologies that are currently used and/or under development; and 4) experiences and lessons learned from real world ontology projects.

Objectives

  • To gain an advanced understanding of and techniques in building knowledge-based information systems for both research and business processes,
  • To familiarize students with knowledge organization structures, markup languages, and tools, and
  • To provide students with practical experience in creating ontologies, thesaurus, and other knowledge organization structures

Who Should Take It

Any graduate student from library and information science, computer science, linguistics, and other relevant disciplines who is interested in knowledge-based information systems should consider taking this course. Students enrolled in this class are expected to have basic understanding of database design, information processing, HTML, and XML. Knowledge and/or experience in programming are not required, but will be helpful. Prereq: IST552 or IST616, or consent from instructor.

Required Textbook

Antoniou, G. & van Harmelen, F. A Semantic Web Primer. Cambrige, Mass.: The MIT Press, 2004.

ISBN: 0-262-01210-3

Coursework

A number of exercises (40%) are designed for better understanding of the theoretical and practical aspects of knowledge organization structures. Students will work in groups for a term project (40%), through which the knowledge and skills learned from class are put in practical problem solving.  Class participation counts for 20% of the total grade.

Expectations and Grading Policy

I try to make every class worth attending (online and in classroom). Students will be responsible for any and all material covered, handed-out, announced, etc. in class unless told otherwise. Attempts will be made, however, to place important announcements in class and/or on the class web site. Lecture notes will be posted on all days as scheduled.

 

Every attempt will be made to return assignments in a timely fashion. Assignments are due on the date indicated, unless specified otherwise. Comments will be made for individual exercises and other submissions with a grade. Late work will be accepted only for two days after the due date, with a 5% penalty per day, unless a legitimate reason for delay is given before hand or an unexpected emergency prevented you from turning in your work on time. This is to facilitate the timely return of graded assignments with answers.

 

This syllabus (including course requirements, due dates, etc.) may be changed with sufficient notice.

 

If you have any type of disability which may require additional time or special consideration, please let me know at the beginning of the course.

 

Grading Policy

  1. According to the grading policy of the School of Information Studies, a "basic grade" will be awarded for student performance that is judged to be satisfactory for the course level (undergraduate or graduate). All other grades will be determined in comparison with the standards of the basic grade. For graduate students the basic grade is B.
  2. Fulfilling the requirements for an assignment coupled with the absence of errors (in writing, arithmetic, formatting) will earn a grade no higher than B+. To earn an A- or A grade, the assignment must go beyond the minimum expected in terms of quality (insight, creativity, analysis, thoroughness, synthesis).
  3. Grade levels follow the scales below:
    A = 94-100, A- = 90-93, B+ = 85-89, B = 80-84, B- = 75-79, C+ = 70-74, C = 65-69, C- = 60-64, F = below 60
  4. An incomplete grade, I, can be given only if the circumstances preventing the on-time completion of all course requirements were clearly unforeseeable and uncontrollable. If an incomplete is required a written contract must be completed which specifies the nature of the missing work, the date it will be completed, and the default grade that will be given if that deadline is missed.
  5. It is unethical to allow some students additional opportunities, such as extra credit assignments, without allowing the same options to all students.
  6. Failure to complete any course requirement will result in a course grade of C or lower, regardless of the grades received in other components.
  7. Group-based assignments will usually have a component of the final grade based on each group member's assessment of the contribution made by the others in the group.
  8. To discuss a grade, arrange for a private meeting in which you identify the sources of your concern. It is important to bring with you to that meeting the relevant materials (e.g., marked papers). Except for extraordinary circumstances, no appeal for an individual assignment or project will be considered later than two weeks after the graded assignment was returned. For final grades, no appeal will be considered after 5/31/2005.
  9. Regular participation in class discussions is expected, exactly as it would be on the job. If an emergency or illness occurs, have someone notify your team and the course instructor as soon as possible--even if you are our of town. If you are going to be absent from team meetings you need to make arrangements to catch-up on what you missed and to make sure your part of the workload is covered. Too little participation is sufficient cause to lower the final course grade. Exceptions will be made for emergencies and other extenuating circumstances provided they are verified by appropriate documentation that is received no later than 1 week after the absence(s).
  10. Academic Integrity
    The academic community of Syracuse University and of the School of Information Studies requires the highest standards of professional ethics and personal integrity from all members of the community. Violations of these standards are violations of a mutual obligation characterized by trust, honesty, and personal honor. As a community, we commit ourselves to standards of academic conduct, impose sanctions against those who violate these standards, and keep appropriate records of violations. For definitions of academic dishonesty and policies and procedures handling academic dishonesty, see http://istweb.syr.edu/academic/courses/administrative/integrity.html

 


Weekly Topics

Week

Topic

Due

1/18

Introduction to the course

  • Topics
  • Technologies
  • Coursework

   

1/25

Knowledge Organization Structures (KOS)

  • A brief history of KOS
  • Classification, taxonomies, thesauri
  • Database schemas, XML schemas
  • Ontologies

     

2/1

Encoding of knowledge organization structures

  • Components in KOS
  • XML and Resource Description Framework (RDF)
  • RDF Schema Language

Exercise 1: Create simple knowledge organization structures 

2/8

Knowledge modeling tools

ˇ         Unified Modeling Language

ˇ         Microsoft Visio

Exercise 2: Use RDF to encode the knowledge structures

2/15

Concepts, properties, and relationships. Part I.

ˇ         Defining concepts: types and vocabulary

ˇ         Properties of concepts 

 

2/22

Concepts, properties, and relationships. Part II.

ˇ         Defining relationships: parent-child, part-whole, etc.

ˇ         Rule definition

ˇ         Knowledge capture

ˇ         Lab: learning how to use Protégé

Exercise 3: Define properties of concepts in the knowledge structures

3/1

 Ontology editor: Protégé

ˇ         Defining classes

ˇ         Defining properties

ˇ         Lab: using Protégé to create an ontology

Exercise 4: Define relationships of concepts in the knowledge structures

3/8

Case study: Open Knowledge Exchange for workforce development

  • Practice: case analysis and knowledge modeling

 

3/15

Spring break

 

3/22

Web Ontology Language: OWL

  • Overview of OWL standards
  • Specifications of OWL

Exercise 5: Case analysis

3/29

Inference rules

ˇ         What are inference rules

ˇ         Components in rules

ˇ         Rule markup in XML

Term project description

4/5

Applications

ˇ         From knowledge model to data model

ˇ         Implementing an ontology into a portal

ˇ         Issues to be considered

Exercise 6: Define inference rules for concepts and relationships

4/12

Interoperability of different knowledge structures

ˇ         Why need interoperability

ˇ         Issues in interoperability

ˇ         Methods of building interoperability

 

4/19

Validation and evaluation of knowledge organization structures

ˇ         Working with users: surveys, interviews, and observations

ˇ         Working with log data: data mining

ˇ         Experiment with prototypes

 

4/26

Wrap-up

 

5/3

Group project presentations

Term project