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Faculty of Information Technology
Department of Computer Systems
Subject Outline
Spring, 2007
32146 – Data & Information Visualization
Number of Credit Points:
6 credit points
Presentation:
The presentation includes 5 Lectures (600 minutes), 5 Tutorials (300
minutes).
The tutorials consist of Discussion Classes and Laboratory Sessions.
At the discussion classes, the tutor explains and discusses exercises
and articles that are related to the previous week's lecture topics.
The discussion classes are intended to reinforce the lecture material
by informal talks, group discussions and student’s organ
presentations. Discussion classes also provide an opportunity for
students to ask questions and seek clarification of lecture topics.
The laboratory sessions are focusing on the guidance of hands on
and practical applications of the data visualization concepts, methods
and techniques, covered in the lectures and discussion sessions.
Assumed Knowledge:
Some experience with human computer interaction, human factors,
graphic design or computer science would be advantageous.
Prerequisites:
32130 Principles & Practice of Data Mining
Corequisites:
None
Handbook Entry:
This subject covers the core data visualization and navigation
technologies that support data mining and knowledge management.
It also provides an essential understanding of the human computer
interaction and human cognition process that are involved in the
design of graphical user interfaces. On successful completion of this
subject, students are capable of designing and evaluating a various
advanced visualization interfaces that can be directly applied to the
fields of visual data mining and web mining.
Objectives:
Visualizing and navigating large amounts of information is a
challenging problem being faced in many IT domains, such as
knowledge discovery and information retrieval. Humans frequently
rely on external cognitive aids such as maps, diagrams, tables and
other visual metaphors to gain a better understanding of the
information. These graphical tools are used not only to facilitate
personal processing and management of information, but also for
communicating mental models and information between humans.
Unfortunately, many of these static aids do not scale to the large and
complex information sources available today. The information
visualization and data mining communities have both made many
exciting technological advancements to address these emerging
demands. These technologies are the focus of this course.
Throughout the term, we will explore the basic principles underlying
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many different visualization techniques, as well as learn the
fundamentals of data navigation through various visual
metaphors. We will examine various systems, tools, techniques and
visual metaphors, and learn how to critique and evaluate the different
approaches.
Moreover we will explore some data mining
applications that have or could potentially benefit from the use of
visualization. We will learn how to develop new and innovative
visualizations to support information exploration, decision making,
communication and information sharing in a variety of domains. The
focus of this course will primarily be on visualizing abstract data that
does not have a geometric or physical correspondence in the
physical world. A detailed list of objectives is shown below.
1. To learn the background knowledge of data & information
visualization technologies in the context of visual data mining;
2. To learn the necessary knowledge of representing and navigating
large information spaces;
3. To learn the state-of-art visual tools, methods and metaphors;
4. To learn how to critique and evaluate the different visualization
approaches;
5. To learn how to develop new and innovative visualizations to
support information exploration, decision making, data mining
and information sharing in a variety of domains;
6. To learn practical knowledge and skills in visualization and
navigation for data mining.
Contribution:
Topics:
Assessment:
This subject provides the latest techniques and skills for the
development of data visualization and interactive visual user-interface
in the context of data mining. On successful completion of this
subject, students are capable of designing and evaluating a various
advanced visualization interfaces that can be directly applied to the
fields of visual data mining and web mining.
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Introduction to Data, Information and Knowledge
Cognition and External Cognitive Aids
Visual Representations of Data and Knowledge
Using 1D, 2D, 3D Spaces for Visual Representation of Data
Interactive Visualization
On-line Visual Query
Zoomable Interfaces
Focus+Context Navigation
Document (text) Visualization
Web Visualization
Using Vision to Think (visual creation)
Visual Collaborative Work Environment
This subject will be assessed by two assignments. The weighting for
each assessment is shown below.
Assignment
Topic
Type
Weight
Week
Issued
Week Due
1. Visualization
Design
Individual
50%
2 (6 Aug)
9 (1 Oct)
2. Technical
Evaluation
Individual
50%
7 (10 Sep)
13 (29 Nov)
Submission: each assessment must be handed in electronically (on a
floppy disk or CD-ROM) or manually before the due dates described
in the above table. Late submissions will not be accepted for
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assessment. Students will be able to check their marks of
assignments online through the subject website and get feedback
(comments) from tutors who marked assignments.
1. Visualization Design (50%)
This assignment requests each student to either design a
visualization to satisfy a list of specific user requirements, or
implement a particular visualization technique based on a given list of
technical issues that are described in the assignment specification.
In the designing stage, students are required to select an appropriate
visual metaphor, design a set of optimized graphical properties and
attributes for the representation of data, and design a particular
navigation scheme that includes the viewing scheme and interaction
scheme.
In the implementation stage, students are required to use one or
more programming languages, such as Java or C++, to create a
particular visualization prototype based on a list of given technical
requirements described in the assignment specification.
The assignment addresses objectives1, 2, 3, 4, 5 and 6. The detail of
the marking scheme will be explained in the assignment
specification.
2. Technical Evaluation (50%)
This assignment requests each student to technically compare two
similar visualization approaches against the aesthetics rules and
other technical measurements. A written evaluation report that
contains precise figures or charts showing the differences between
these two approaches is required.
The assignment addresses objectives 1, 2, 3, 4, 5 and 6. Students
are required to work in a group of two or three. The detail of the
marking scheme will be explained in the assignment specification.
Online Support:
The following URL is the website that provides online support for
teaching and learning of this subject:
http://staff.it.uts.edu.au/~maolin/32146_DIV/
The support includes on-line curriculum, on-line tutorial, on-line
notice/news, on-line assignment specifications and on-line mark
checking.
References:
There are four recommended reference books that cover the most of
units to be taught in the course. They are:
1. Card, S. K., MacKinlay, J. D., Shneiderman, B., (2000)
Readings in Information Visualization: Using Vision to
Think, Morgan Kaufmann, ISBN 1-55860-533-9
2. Colin Ware (2000) Information Visualization: Perception for
Design, Morgan Kaufmann, ISBN 1-55860-511-8
3. Geroimenko, V. & Chen, C., (2002) Visualizing the Semantic
Web, Springer-Verlag, London, ISBN 1-85233-576-9
4. Chaomei Chen (1999) Information Visualization and Virtual
Environments, Springer-Verlag, London, ISBN 1-85233-136-4
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Online material will be available to support aspects of the subject.
Subject Coordinator:
Dr Mao Lin Huang
Faculty of IT, UTS
PO Box 123 Broadway NSW 2007
Email: [email protected]
The subject coordinator may be contacted by email or phone if you
have matters of a personal nature to discuss, e.g., illness, study
problems, team problems, team re-assignment, or a request for an
appointment outside the given consultation hours. All email must
bear a meaningful description in the ‘Subject’ box at the top of the
email, beginning with the subject number: e.g., 3xxxx team
problems, 3xxxx request for late submission due to illness, 3xxxx I
have no team, etc.
Generally questions regarding assessment and the subject should
be raised in the lectures or tutorials. This ensures that all students
get the benefit of the information given. Emails that are considered
better answered in class may not receive a response.
Assessor:
Dr Andrew Solomon
Office: CB10.04.433
Phone: 9514 7938
Email: [email protected]
Assessors are nominated within the Faculty by the Responsible
Academic Officer (RAO). Assessors are responsible for ensuring that
the Subject Outline and assessment for a subject are appropriate and
reasonable. In this role, assessors liaise with Subject Coordinators,
not Students directly.
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Academic Standards:
Students are reminded of the principles laid down in the Faculty’s
Statement of Academic Integrity - Good Practice and Ethics in
Informal Assessment found at;
<wiki.it.uts.edu.au/start/Academic_Integrity>.
The University’s rules regarding academic misconduct can be
found at; <www.gsu.uts.edu.au/rules/16-2.html>
Assignments in this Subject should be your own original work. The
inclusion in assessable work of any material such as code,
graphics or essay text obtained from other persons or sources
without citation of the source is plagiarism and is a breach of
University Rule 16.2.2.
Any collaboration with another person should be limited to those
described in the “Acceptable Behaviour” section of the Statement
of Academic Integrity. Similarly, any group work should be the
result of collaboration only within the group. Any infringement by a
student will be considered a breach of discipline and will be dealt
with in accordance with the Rules and By-Laws of the University.
Students are not to give to or receive from any other persons
copies of their assessable work in any form (hard copy or an
electronic file). To do so is 'academic misconduct' and is a breach
of University Rule 16.2.2. That is, assisting other students to cheat
or to act dishonestly in a submitted assignment.
Accidental submission of another students work as your own is
considered to be a breach of University Rule 16.2.2 in that you are
acting dishonestly since you should not have a copy of another
student's work.
The Faculty penalty for proven and serial misconduct of this
nature is zero marks for the Subject. For more information go
to;
<wiki.it.uts.edu.au/start/Academic_Integrity >.
ELSSA:
If you think you need help with your English, or feel unable to
express yourself correctly in assignments, contact the English
Language Study Skills Assistance (ELSSA) Centre, Level 18
Tower Building, Broadway, phone 9514-2327.
ALO:
Academic Liaison Officers’ (ALO) are academics who help
students with special needs (students with temporary or permanent
disabilities, students with language problems who are from nonEnglish speaking backgrounds, or students who are primary
carers).
If you require assistance with assessment tasks and exams, the
Faculty ALO will help you negotiate special conditions with your
Lecturers. For example;
• the use of a dictionary and extra time in exams if your first
language is not English (only available for your first two years at
UTS)
• tests and exams printed in larger type if you have a vision
impairment
• use of a lap-top if you cannot write because of an injury
• extra time to complete assignments if your studies have been
disrupted by illness or disability.
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If you require it, the ALO will talk to all your Lecturers so that you
don't have to explain your circumstances to each of them
individually. Privacy is important and personal information is only
passed on to university staff on a "need to know" basis. Students
with disabilities are encouraged to contact the Special Needs
Service for advice before contacting the ALO.
The Faculty ALO is Dr Jim Underwood, Program Director BScIT,
who can be contacted by email <[email protected]>
or phone 9514 1831.
Student support:
Information regarding support available to students undertaking
this Subject is available at;
<wiki.it.uts.edu.au/start/Student_Support>
Support for learning and teamwork skills is available at;
<www.bell.uts.edu.au> and <www.star.uts.edu.au>
Having problems?
If you are experiencing problems while undertaking this Subject
then help and assistance are available both within the Faculty and
also within the wider University. More information is at;
<wiki.it.uts.edu.au/start/Student_Support >.
You should attempt to resolve the problem through the following
chain: 1. Tutor, 2. Lecturer, 3. Subject Coordinator, 4. Head of
Department, and finally 5. the Responsible Academic Officer,
(Associate Dean Education)
Student Attendance
The Faculty of Information Technology expects that students will
attend all scheduled sessions for a Subject in which they are
enrolled.
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Dates
Week
Number
30 July Week 1
06 Aug Week 2
13 Aug Week 3
20 Aug Week 4
Modules
Lectures/Tutorials
Introduction to Data,
Information and
Knowledge
Cognition and External
Cognitive Aids
Visual Representations
of Data and Knowledge
Using 1D, 2D, 3D
Spaces for Visual
Representation of Data
CB01.02.240
CB01.02.240
No Class : Self
directed learning
Interactive Visualization
03 Sep Week 6
Tutorial Week
No Class : Self
directed learning
No Tutorial
10 Sep Week 7
On-line Visual Query
CB01.02.240
24 Sep Break
01 Oct
Week 9
08 Oct
Week 10
15 Oct
Week 11
22 Oct
Week 12
29 Oct
Week 13
Assignment 1
Handout
No Class : Self
directed learning
27 Aug Week 5
17 Sep Week 8
Assignments
No Class : Self
directed learning
Vice- Chancellor’s Week No Tutorial
Focus+Context
CB01.02.240
Navigation
Document (text)
No Class : Self
Visualization
directed learning
No Class : Self
Web Visualization
directed learning
Using Vision to Think
No Class : Self
(visual creation)
directed learning
Visual Collaborative
CB01.02.240
Work Environment
Assignment 2
Handout
Zoomable Interfaces
05 Nov Week 14
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Assignment 1
Submission
Assignment 2
Submission