Computer Science 455/826 - Information Modeling and Retrieval
This course focuses on the planning for and management of complex
state of the art information systems. Topics include: capturing and
producing
information; evaluating, enhancing, and protecting the value of
information; independent and interdependent information systems; and
the support and
management of information infrastructures.Course Offering
The details of the current course offering can be found here.
Information systems can either maintain the status
quo (and thus be considered only as a necessary cost item) or go beyond
it to add value to the organization. Considering the rapid evolution in
the state of the art and the state of the practice, maintaining the
status quo generally results in falling behind the competition. It is
important that both computer professionals and computer consumers
recognize that
information resource management is increasingly important in the
success not only
of individual information systems but also of the whole organization.
This course will investigate the main aspects
necessary for organizational information resource management and
creative
techniques for profitably managing information resources.
- CMPT 455 requires CMPT 355 as a prerequisite.
- CMPT 826 is available to graduate students
with
the permission of the instructor.
Jim Carter
<carter@cs.usask.ca> 280.3 Thorvaldson 966-4893
There is no single published source of information that is up to
date
with the full range of topics for this course. Rather than purchase a
book
that is either dated or incomplete, students will be provided with a
set
of links to various Web based resources. It is essential that students
keep up with the readings in advance
of the classes where they are to
be discussed. [NOTE: the listing of readings in the Course Outline are subject to
revision up to the Friday prior to the week for which they are listed.
In many cases more readings are listed than will actually be assigned.]
Readings are available via direct links, where possible, or available
to students who log into the University
of
Saskatchewan
Library [where bibliographic information is
provided]
Tues / Thurs 1:00 - 2:20 in ______________
The role of the lecture sessions is to present and discuss important
material related to the weekly topics. - The first class of the week will focus on a discussion of items of
particular interest to class members identified in the critiques
submitted by the students. The second class will focus on a survey of other relevant issues
related to the week's topic.
- Students will be
responsible
for all material covered in the class lecture sessions. Because of the discussion-based format of the class, attendance is
important.
- 10% of the term mark will be based on active, productive class
participation.
Because of the complex nature of the systems and techniques being
studied,
it is impractical for this course to involve major systems development
activities
such as are found in most other computer science courses.
Rather than spending excessive amounts of time developing only a few
complex
system components, the course focuses on a variety of principles and
techniques
that would facilitate developments for a wider range of instances.
- Assignments will take the form of weekly critiques of relevant
papers.
- A major project will encourage students to investigate a related
topic in greater detail than is covered in the class. Students will be
required to make a short presentation about their project in class.
Both the critiques and the project will require students to
investigate
information beyond that contained in the text and lectures. Students
will
be expected to conduct these investigations using both the Web and the
University
library. In some cases, these investigations may be enhanced by
personal
consultations with active professionals.
NOTE: Students taking this course as an 826 will be expected
to
do more advanced work than required of students taking it as 455.
- 10% Class Participation
- 20% Critiques
- 40% Term Project
- 05% Project Proposal
- 15% Project Analysis and
Design
- 15% Project Implementaiton and
Evaluation
- 05% Class Presentation
- 30% Final Exam
[Dates, Topics, and Readings are subject to change]
Week
|
Topics
|
Readings
(Papers to critique are identified by bold type) |
|
Issues |
|
1
S 7, 11
|
- Introduction
Structure and operations of this course
Information as a valuable resource
Information based business
Identifying information resources
|
Main
paper
for
1st
class:
[notes]
R.Y. Wang & D.M. Strong, Beyond
accuracy: What data
quality means
to data consumers [Journal of Management Information Systems,
12(4):5-34, Spring 1996]
Main paper to read for
2nd class: [notes]
R. Evernden and E. Evernden, Third-Generation
Information
Architecture
|
2
S 14, 16
|
Information Economics
Volatility in the value
of information:
The influence of time on information value The influence of exclusivity on information value
Beyond operational
information: Private and public informationInformation products and servicesOrganizational memory
|
Main
paper
to
critique:
[critiques]
J.B. DeLong &
A.M. Froomkin, Speculative
Microeconomics
for
Tomorrow's
Economy
Main paper to read for 2nd
class: [notes]
H.R. Varian, Versioning
Information
Goods
Additional papers:
Computer Science and Telecommunications Board, Appendix
D
-
Information
Economics:
A
Primer
J. Conklin, Designing
Organizational Memory: Preserving Intellectual Assets in a Knowledge
Economy
|
|
Approaches
|
|
3
S 21, 23
|
Information
and
Users
Mapping and exploring I & U:
Identifying users of information
Identifying information needs of users
User related information management:
Information based organizational restructuring
Increasing efficiency via reducing redundancy
Increasing accuracy via centralization
Increasing accessibility via distribution
|
Main
paper
to
critique:
[notes]
Lars-Erik Axelsson, Identify
User
Profiles
in
Information
Systems
with
Unknown
Users - A Database
Modeling Approach
Main paper to read for
2nd
class: [notes]
Iain Barker, What
is information architecture
Additional papers:
James C. Brancheau, Larry Schuster, Salvatore T. March,
Building and implementing an information architecture [ACM SIGMIS Database,
20(2):9-17, Summer 1989]
|
4
S 28, 30
|
Information
and
Tasks
Mapping and exploring I & T:
identifying information needs of tasks
identifying opportunities for information
Information driven task opportunities:
Information to support
operational, tatical, and strategic
tasks
Information to support conflicting needs
(Business Process Re-engineering)
|
Main
paper
to
critique:
[notes]
W.J. Kettinger, Information
Architectural
Design
in
Business
Process
Reengineering [Journal of Information
Technology, 11(1):27-37, March 1996]
Main paper to read for
2nd
class:
[notes] [more
notes]
E.G. Toms, Information
Interaction: Providing a Framework for
Information Architecture
Additional papers:
K.J. Fadel, A Knowledge-Centric Framework for Process
Redesign [Proc.2005 ACM SIGMIS CPR, 49-58]
|
|
Technologies |
|
5
O 5, 7
|
Semantic
Data
Modeling
-
Theory
Ontologies,
Classifications, Taxonomies |
Main
paper
to
critique:
[questions
to
discuss]
V.C. Storey, Understanding
Semantic
Relationships [Very
Large Data Bases, 2(4):455-488, October 1993]
Main paper to read for 2nd
class: [notes]
V.C. Storey, Comparing Relationships in Conceptual
Modeling:
Mapping to Semantic Classifications [IEEE Trans on Knowledge and Data
Engineering, 17(11):1478-1489, November 2005]
Additional papers:
P. Spyns, R.
Mersmann, & M. Jarrar, Data
modelling
versus
Ontology
engineering
R. Prieto-Díaz, A
Faceted
Approach
to
Building
Ontologies
A. Marradi, Classification,
Typology,
Taxonomy
M. Jarrar, J. Demey & R. Meersman, On
Using
Conceptual
Data
Modeling
for
Ontology
Engineering
|
6
O 12, 14
|
Semantic
Data
Modeling
-
Practice
Ontology Engineering
XML, RDF, OWL
|
Main
paper
to
critique:
[questions
and
notes]
"Chapter I - The
Syntactic and the Semantic Web" from Semantic
Web
Services:
Theory,
Tools
and
Applications by Jorge Cardoso
(ed), 2007, available from Books 24 x 7 via the University
of Saskatchewan Library
Main paper to read for 2nd
class: [notes]
"Chapter Seven - Resource Description Framework (RDF)" and "Chapter
Eight - Web Ontology Language (OWL)" from Developing Semantic Web Services by
H. Peter Alesso and Craig F. Smith, 2005, available from Books 24 x 7
via the University
of Saskatchewan Library
Additional Papers:
"Chapter I - Overview of
Semantic Technologies" from Handbook
of Ontologies for Business Interaction by Peter Rittgen (ed),
2008, available from Books 24 x 7 via the University
of Saskatchewan Library
"Chapter 2 - Ontologies " from Model
Driven Architecture and Ontology Development by Dragan Gaševic,
Dragan Djuric and Vladan Devedzic, 2006, available from Books 24 x 7
via the University
of Saskatchewan Library
|
| O 15 |
****
Project
Proposal Due |
|
7
O 19, 21 |
Dimensional
Data
and
Data
Warehouses
-
Introduction
Multidimensional Data
Operational vs archival data
Data warehouses
|
Main
paper
to
critique:
J. Trujillo, M. Palomar, J. Gomez & I.-Y. Song, Designing Data
Warehouses with OO Conceptual Models [notes]
Additional paper to read for 2nd class:
M.E. Jones & I.-Y. Song, Dimensional modeling:
Identification, classification, and evaluation of patterns [Decision
Support Systems, 45(1):59-76, April 2008] |
8
O 26, 28
|
Dimensional
Data
-
Practice
Dimensional Model Design Life Cycle
Data
Warehousing and Integration
|
Main paper to critique:
"Chapter
6 - Dimensional Model Design Life Cycle" from Dimensional Modeling: In a Business
Intelligence Environment by Chuck Ballard et al., 2006,
available from Books 24 x 7 via the University
of
Saskatchewan
Library
Main paper to read for 2nd
class: [notes]
"Chapter I - Conceptual Modeling Solutions for the
Data Warehouse " from Data Warehouses and OLAP: Concepts, Architectures
and Solutions by Robert Wrembel and Christian Koncilia (eds) 2007,
available from Books 24 x 7 via the University
of
Saskatchewan
Library
Additional papers: [NOTE:
each of these papers introduces a
different
issue. we will focus our discussion on the issues introduced and not on
the entirety of these papers]
E. Rahn & H.H. Do, Data
Cleaning:
Problems
and
Current
Approaches
T. Harder, G. Sauter, & J. Thomas, The intrinsic problems
of structural heterogeneity and an approach to their solution [VLDB
Journal 8(1):25–43, April 1999]
R. Hull, Managing
Semantic
Heterogeneity
in
Databases:
A
Theoretical
Perspective
|
9
N 2, 4
|
OLAP
Analyzing Dimensional Data
OLAP On-line Analytical Processing
|
Main
set
of
papers
to
critique:
[critiques]
J. Horner, I-Y Song, P.P. Chen, An Analysis of Additivity
in
OLAP Systems [Proceedings of the 7th ACM
international workshop on Data warehousing and OLAP
Main paper to read for 2nd
class: [notes]
N. Gorla, Features to Consider in a Data Warehousing System
[Communications of the ACM 46(11):111-115, November 2003]
Additional papers: [NOTE: each
of these papers introduces a different issue. we will focus our
discussion on the issues introduced and not on the entirety of these
papers]
WWW.Olapreport.com
* What
is
OLAP?
* OLAP applications
* OLAP architectures
* Database
explosion
T. Priebe & G. Pernul,
Ontology-based Integration of OLAP and Information Retrieval [IEEE
Proceedings of the 14th International Workshop on Database and Expert
Systems Applications (DEXA’03)]
|
10
N 9 |
- Data Mining
Data mining in databases and data warehouses - Data mining on the Web
|
Main
paper
to
critique:
[critiques]
M. Goebel and L. Gruenwald, A
Survey
Of
Data
Mining
And
Knowledge
Discovery
Software Tools
Main paper to read for class: [notes]
K. Collier, B. Carey, D. Sautter and C. Marjaniemi, A
Methodology for Evaluating and Selecting Data Mining Software
Additional general paper:
"Chapter 1 - Introduction to Data Mining" from Discovering Knowledge in Data: An
Introduction to Data Mining by Daniel T. Larose, 2005,
available from Books 24 x 7 via the University
of
Saskatchewan
Library
Additional papers: [NOTE: each of these papers introduces a
different
issue. we will focus our discussion on the issues introduced and not on
the entirety of these papers]
L. Geng & H.J.
Hamilton, Interestingness Measures for
Data Mining: A Survey [ACM Computing Surveys, 38(3) September 2006]
M. Song & W.M.P. van der Aalst, Towards Comprehensive
Support for Organizational Mining [Decision Support Systems,
40(1):300-317, December 2008]
R. Cooley, B. Mobasher, and J. Srivastava, Web
Mining:
Information
and
Pattern
Discovery
on
the
World Wide Web
"Chapter I - Introduction to Text Mining" from The Text Mining Handbook: Advanced
Approaches in Analyzing Unstructured Data by Ronen Feldman and
James Sanger, 2007,
available from Books 24 x 7 via the University
of
Saskatchewan
Library |
| N 12 |
****
Project Analysis and Design
Due |
|
11
N 16, 18 |
Finding
Information
Advanced queries
Dynamic queries
Searching on the Web
Domain specific limited Natural Language
|
Main
paper
to
critique:
[notes] [critiques]
C.C. Kuhlthau, Inside
the
Search Process: Information Seeking
from the User’s Perspective [Journal of the American Society for
Information Science 42(5):361-371, 1991]
Additional papers: [NOTE: each
of these papers introduces a different
issue. we will focus our discussion on the issues introduced and not on
the entirety of these papers] [notes]
C. Jermaine, Su Arumugam, A. Pol & A. Dobra, Scalable
Approximate Query Processing with the DBO Engine, [ACM Transactions on
Database Systems, 33(4): Article 23, November 2008]
T. Eiter, M. Fink, G. Greco & D.L. Sapienza, Repair
Localization for Query Answering from Inconsistent Databases [ACM
Transactions on Database Systems, 33(2): Article 10, June 2008]
Y. Tao & D. Papadias, Spatial Queries in Dynamic
Environments, [ACM Transactions on Database Systems, 28(2):101–139,
June 2003]
G. Karvounarakis, A. Magganaraki, S. Alexaki, V.
Christophides, D. Plexousakis, M. Scholl, and K. Tolle, Querying the
Semantic Web with RQL [Computer Networks, 42(5):617-640, August 2003]
T. Cheng & K. C.-C. Chang, Entity
Search
Engine:
Towards
Agile
Best-Effort
Information
Integration
over
the Web
R.W. White & S.M. Drucker, Investigating
Behavioral
Variability
in
Web
Search
M. Maybury, Human
Language
Technologies
for
Knowledge
Management:
Challenges
and
Opportunities
|
12
N 23, 25 |
Visual
Data and Data
Visualization
Visualization techniques
Visualization tools |
Main
paper
to
critique:
[critiques]
I. Herman, Graph
Visualization and Navigation in
Information
Visualization: A Survey [IEEE Transactions on Visualization and
Computer Graphics, 6(1):24-43, January-March 2000]
Additional papers: [NOTE:
each of these papers introduces a
different
issue. we will focus our discussion on the issues introduced and not on
the entirety of these papers] [notes]
R. Lenger and M.J. Eppler, Towards
A
Periodic
Table
of
Visualization
Methods
for
Management
H.-J. Schulz, T. Nocke, H. Schumann, A
Framework
for
Visual
Data
Mining
of
Structures
R. Amar and J. Stasko, A
Knowledge Task-Based Framework for Design and Evaluation of Information
Visualizations
E.R.A. Valiati, M.S. Pimenta & C.M.D.S. Freitas, A
Taxonomy of Tasks for Guiding the Evaluation of Multidimensional
Visualizations [ACM Proceedings of the 2006 AVI workshop on BEyond time
and errors: novel evaluation methods for information visualization]
M. Tory & T. Moller, Rethinking
Visualization:
A
High-Level
Taxonomy |
N 26
|
****
Project Implementation and
Evaluation Due
|
|
13
N 30, D 2
|
Student
Presentations
Take-home Final
Distributed
|
|
|
|
|
|