Class News: Updated July 5 [Welcome]
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.
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.
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]
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.
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.
- 05% Project Proposal
- 15% Project Analysis and Design
- 15% Project Implementaiton and Evaluation
- 05% Class Presentation
[Dates, Topics, and Readings are subject to change]
| Week |
Topics
|
Readings (Papers to critique are identified by bold type) |
| Issues | ||
| 1 S 7, 11 |
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 |
Volatility in the value of information:
|
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: User related information management: |
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: Information driven task opportunities: |
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 |
|
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 |
|
Date of last revision: July 6, 2010