LIBR 246-05
LIBR 246-15
Information Technology Tools and Applications – Advanced Topic: Information Visualization
Spring 2014 Greensheet

Dr. Michelle Chen

Office Hours: 
Virtually, by appointment via e-mail or Blackboard IM. Blackboard Collaborate optional drop-in office hours will also be held as needed. More details TBA on the Canvas course website.

Greensheet Links
Canvas Login and Tutorials
iSchool eBookstore

Canvas Information: This course will be available beginning Thursday, January 23rd, 12AM PST. You will be enrolled into the site automatically.

Course Description

Current information professionals are faced with an overwhelming amount of information every day. The information is typically unstructured, abstract, large-scale, and needs a more efficient and intuitive way to represent the relationships, reveal the patterns, and/or discover potential opportunities. Information visualization has thus recently gained increasing attention and begun to be widely applied to scientific, engineering, and social disciplines to help people understand and present their information better. According to Gershon et al. (1998), visualization can provide "an interface between two powerful information processing systems - human mind and the modern computer."

This course focuses on the state of the art in the field of information visualization. Topics include:

  1. The background of information visualization;
  2. Perceptual and design principles of information visualization;
  3. Data analysis methods and hands-on applications of visualization techniques;
  4. Interaction and interface design issues; and
  5. Exciting emerging trends applied to library and information science fields such as social visualization and storytelling.

The ultimate goal of this course is to provide technical and non-technical students with an alternative powerful tool to process information in the specific domain of their own interests.

Course Requirements


  • Participation and Discussions (10%, supports SLO#1, SLO#2, SLO#3, SLO#4)
    Students are required to actively participate in class and make thoughtful contributions to two class discussions posted on the course website. Students will be evaluated for the involvement in and intellectual contribution to the collaborative learning environment.
  • Homework Assignments (60%, supports SLO#1, SLO#2, SLO#3)
    Four individual assignments (equally weighted) will be given throughout the semester to help students review and reinforce what they have learned in class. Assignments contain a mixture of written and hands-on practices.
  • Review Quiz (10%, supports SLO#1, SLO#2, SLO#3)
    One mid-semester quiz will be given to help students better understand the course contents and keep up with the class progress. This open-book quiz will be conducted on the Canvas course website during week 8 and will contain five questions. More details will be announced on Canvas.
  • Semester Project (20%, supports SLO#4)
    Students are expected to work in groups (created in week 4) on a semester project and deliver a project report (10%) and an asynchronous presentation (10%) via Collaborate in the final class week (i.e., week 16). Students will have two options (more details TBA on the Canvas course website):
    • Practice visualization techniques with an interesting data set in a particular setting and present the results and critiques; or
    • Relate what we learned in class to students' own professions and present how visualization can be used to enhance their data analysis and discovery process.

Course Calendar (subject to change with fair notice)

Weeks Topics and Due Dates
Week 1
Jan 23-26
Introduction to Information Visualization
Week 2
Jan 27 - Feb 2
Data Analysis and Table/Graph Design
Week 3
Feb 3 - Feb 9
Perceptual Properties
Homework #1 Due Feb 9
Week 4
Feb 10 - Feb 16
Multivariate Visual Representations
Week 5
Feb 17 - Feb 23
Visualization Design Principles
Homework #2 Due Feb 23
Week 6
Feb 24 - Mar 2
Week 7
Mar 3 - Mar 9
Visualization Systems, Tools, and Demos
Discussion #1 Due Mar 9
Week 8
Mar 10 - Mar 16
Review Quiz
Week 9
Mar 17 - Mar 23
Week 10
Mar 24 - Mar 30
Spring Break - No Class
Week 11
Mar 31 - Apr 6
Graphs and Networks Visualization
Homework #3 Due Apr 6 
Week 12
Apr 7 - Apr 13
Hierarchies and Trees Visualization
Week 13
Apr 14 - Apr 20
Time Series Visualization
Homework #4 Due Apr 20
Week 14
Apr 21 - Apr 27
Social Visualization
Discussion #2 Due Apr 27
Week 15
Apr 28 - May 4
Visual Analytics
Week 16
May 5 - May 13
Project Presentations (asynchronous)
Project Report Due May 13


Deliverable Points (Total = 100)
Participation and Discussions Discussion #1: 5
Discussion #2: 5 
Homework Assignments Homework #1: 15
Homework #2: 15
Homework #3: 15
Homework #4: 15 
Review Quiz 10
Semester Project Project Report: 10
Presentation: 10 

All assignments must be submitted by 11:59PM (PST) on the day the assignment is due. Late assignments will be reduced by 20% of point value per day late. Please contact Dr. Chen if a medical or a family/personal emergency prevents you from submitting an assignment on time. Details of the quiz and semester project will be given on Canvas course website.

Course Workload Expectations

Success in this course is based on the expectation that students will spend, for each unit of credit, a minimum of forty-five hours over the length of the course (normally 3 hours per unit per week with 1 of the hours used for lecture) for instruction or preparation/studying or course related activities including but not limited to internships, labs, clinical practica. Other course structures will have equivalent workload expectations as described in the syllabus.

Instructional time may include but is not limited to:
Working on posted modules or lessons prepared by the instructor; discussion forum interactions with the instructor and/or other students; making presentations and getting feedback from the instructor; attending office hours or other synchronous sessions with the instructor.

Student time outside of class:
In any seven-day period, a student is expected to be academically engaged through submitting an academic assignment; taking an exam or an interactive tutorial, or computer-assisted instruction; building websites, blogs, databases, social media presentations; attending a study group;contributing to an academic online discussion; writing papers; reading articles; conducting research; engaging in small group work.

Course Prerequisites

LIBR 202, other prerequisites may be added depending on content

Student Learning Outcomes

Upon successful completion of the course, students will be able to:

  1. Define the basic syntax of coding PHP programs.
  2. Use HTML forms with PHP.
  3. Use standard PHP functions and be able to write their own custom functions.
  4. Demonstrate a basic understanding of MySQL and be able to use it in a PHP program.
  5. Build and maintain a small Web application.
  6. Identify the features of JavaScript.
  7. Incorporate JavaScript/Jscript into HTML using current versions of popular Internet browsers.
  8. Identify the types of data and operators in JavaScript.
  9. Incorporate variables in JavaScript.
  10. Declare functions and add objects along with their methods and properties in JavaScript.
  11. Manage JavaScript events by using event handlers.
  12. Create interactive HTML forms by applying the properties and methods of form objects and elements.
  13. Implement loops in JavaScript programs.
  14. Manipulate the images displayed on a Web page.
  15. Identify how information about a Web page is stored.
  16. Identify the functions of cookie attributes; create and manipulate cookies.
  17. Identify information provided by navigator object properties.
  18. Manipulate strings using the string object method.

Core Competencies (Program Learning Outcomes)

LIBR 246 supports the following core competencies:

  1. E Design, query and evaluate information retrieval systems.
  2. G Demonstrate understanding of basic principles and standards involved in organizing information, including classification, cataloging, metadata, or other systems.
  3. H Demonstrate proficiency in identifying, using, and evaluating current and emerging information and communication technologies.


Required Textbooks:

  • Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Analytics Press. Available through Amazon: 0970601980arrow gif indicating link outside sjsu domain

Grading Scale

The standard SJSU School of Information Grading Scale is utilized for all iSchool courses:

97 to 100 A
94 to 96 A minus
91 to 93 B plus
88 to 90 B
85 to 87 B minus
82 to 84 C plus
79 to 81 C
76 to 78 C minus
73 to 75 D plus
70 to 72 D
67 to 69 D minus
Below 67 F


In order to provide consistent guidelines for assessment for graduate level work in the School, these terms are applied to letter grades:

  • C represents Adequate work; a grade of "C" counts for credit for the course;
  • B represents Good work; a grade of "B" clearly meets the standards for graduate level work;
    For core courses in the MLIS program (not MARA) — INFO 200, INFO 202, INFO 204 — the iSchool requires that students earn a B in the course. If the grade is less than B (B- or lower) after the first attempt you will be placed on administrative probation.  You must repeat the class the following semester. If -on the second attempt- you do not pass the class with a grade of B or better (not B- but B) you will be disqualified.
  • A represents Exceptional work; a grade of "A" will be assigned for outstanding work only.

Students are advised that it is their responsibility to maintain a 3.0 Grade Point Average (GPA).

University Policies

General Expectations, Rights and Responsibilities of the Student

As members of the academic community, students accept both the rights and responsibilities incumbent upon all members of the institution. Students are encouraged to familiarize themselves with SJSU's policies and practices pertaining to the procedures to follow if and when questions or concerns about a class arises. See University Policy S90-5 at More detailed information on a variety of related topics is available in the SJSU catalog at In general, it is recommended that students begin by seeking clarification or discussing concerns with their instructor. If such conversation is not possible, or if it does not serve to address the issue, it is recommended that the student contact the Department Chair as a next step.

Dropping and Adding

Students are responsible for understanding the policies and procedures about add/drop, grade forgiveness, etc. Refer to the current semester's Catalog Policies section at Add/drop deadlines can be found on the current academic year calendars document on the Academic Calendars webpage at The Late Drop Policy is available at Students should be aware of the current deadlines and penalties for dropping classes.

Information about the latest changes and news is available at the Advising Hub at

Consent for Recording of Class and Public Sharing of Instructor Material

University Policy S12-7,, requires students to obtain instructor's permission to record the course and the following items to be included in the syllabus:

  • "Common courtesy and professional behavior dictate that you notify someone when you are recording him/her. You must obtain the instructor's permission to make audio or video recordings in this class. Such permission allows the recordings to be used for your private, study purposes only. The recordings are the intellectual property of the instructor; you have not been given any rights to reproduce or distribute the material."
    • It is suggested that the syllabus include the instructor's process for granting permission, whether in writing or orally and whether for the whole semester or on a class by class basis.
    • In classes where active participation of students or guests may be on the recording, permission of those students or guests should be obtained as well.
  • "Course material developed by the instructor is the intellectual property of the instructor and cannot be shared publicly without his/her approval. You may not publicly share or upload instructor generated material for this course such as exam questions, lecture notes, or homework solutions without instructor consent."

Academic integrity

Your commitment, as a student, to learning is evidenced by your enrollment at San Jose State University. The University Academic Integrity Policy F15-7 at requires you to be honest in all your academic course work. Faculty members are required to report all infractions to the office of Student Conduct and Ethical Development. The Student Conduct and Ethical Development website is available at

Campus Policy in Compliance with the American Disabilities Act

If you need course adaptations or accommodations because of a disability, or if you need to make special arrangements in case the building must be evacuated, please make an appointment with me as soon as possible, or see me during office hours. Presidential Directive 97-03 at requires that students with disabilities requesting accommodations must register with the Accessible Education Center (AEC) at to establish a record of their disability.

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