Information Technology Tools and Applications – Advanced Topic: Information Visualization
Spring 2015 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.
Canvas Login and Tutorials
Canvas Information: Courses will be available beginning January 22nd, 12:01am PST unless you are taking an intensive or a one unit or two unit class that starts on a different day. In that case the class will open at 12:01am PST on the first day that the class meets.
You will be enrolled into the Canvas site automatically.
Be sure to logon to the course site no later than Friday, January 23, to begin the first lesson.
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:
- The background of information visualization;
- Perceptual and design principles of information visualization;
- Data analysis methods and hands-on applications of visualization techniques;
- Interaction and interface design issues; and
- Exciting emerging trends applied to library and information science fields such as social visualization and visual analytics.
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.
- 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 (65%, supports SLO#1, SLO#2, SLO#3)
Five 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.
- Semester Project (25%, supports SLO#4)
Students are expected to work individually or in groups (TBD in week 4) on a semester project and deliver a mini report (5%), a final project report (10%), and a final, asynchronous project presentation (10%). Students will have two options for the semester project (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, discovery, interpretation, and communication process.
Course Calendar (subject to change with fair notice)
|Weeks||Topics and Due Dates|
|Introduction to Information Visualization|
Jan 26 - Feb 1
|Data Analysis and Table/Graph Design|
|Perceptual Properties for Visualization
Homework #1 Due Feb 8
|Multivariate Visual Representations|
|Tufte's Design Principles
Homework #2 Due Feb 22
Feb 23 - Mar 1
|Visualization Software and Tools|
|Storytelling with Information Visualization
Discussion #1 Due Mar 8
Mini Report Due Mar 8
|Guest Lecture: Information Visualization
for Digital Archiving and Preservation
(Dr. Maria Esteva, Research Associate/Data Archivist,
Texas Advanced Computing Center)
Homework #3 Due Mar 22
Mar 30 - Apr 5
|Visualization for Graphs and Networks
Homework #4 Due Apr 5
|Visualization for Hierarchies and Trees|
|Visualization for Time Series
Homework #5 Due Apr 19
Discussion #2 Due Apr 26
Apr 27 - May 3
|Final Project Presentations
Project Presentation and Report Due May 13
|Deliverable||Points (Total = 100)|
|Discussions||Discussion #1: 5
Discussion #2: 5
|Homework Assignments||Homework #1: 13
Homework #2: 13
Homework #3: 13
Homework #4: 13
Homework #5: 13
|Semester Project||Mini Report: 5
Final Report: 10
Final 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 discussion topics, assignments, and semester project will be given on the 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.
LIBR 202, other prerequisites may be added depending on content.
Student Learning Outcomes
Upon successful completion of the course, students will be able to:
- Describe the perceptual and cognitive principles of information visualization.
- Use data analysis methods and visualization tools to manage and analyze large collections of abstract information.
- Identify interaction and interface design issues in visualization.
- Apply visualization techniques to specific domains of their own interests for knowledge discovery and retrieval.
Core Competencies (Program Learning Outcomes)
LIBR 246 supports the following core competencies:
- E Design, query and evaluate information retrieval systems.
- H Demonstrate proficiency in identifying, using, and evaluating current and emerging information and communication technologies.
- Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Oakland, CA: Analytics Press. Available through Amazon: 0970601980
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|
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).
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 http://www.sjsu.edu/senate/docs/S90-5.pdf. More detailed information on a variety of related topics is available in the SJSU catalog at http://info.sjsu.edu/web-dbgen/catalog/departments/LIS.html. 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 http://info.sjsu.edu/static/catalog/policies.html. Add/drop deadlines can be found on the current academic year calendars document on the Academic Calendars webpage at http://www.sjsu.edu/provost/services/academic_calendars/. The Late Drop Policy is available at http://www.sjsu.edu/aars/policies/latedrops/policy/. 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 http://www.sjsu.edu/advising/.
Consent for Recording of Class and Public Sharing of Instructor Material
University Policy S12-7, http://www.sjsu.edu/senate/docs/S12-7.pdf, 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."
- "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."
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 http://www.sjsu.edu/senate/docs/F15-7.pdf 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 http://www.sjsu.edu/studentconduct/.
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 http://www.sjsu.edu/president/docs/directives/PD_1997-03.pdf requires that students with disabilities requesting accommodations must register with the Accessible Education Center (AEC) at http://www.sjsu.edu/aec to establish a record of their disability.
Download Adobe Acrobat Reader to access PDF files.
More accessibility resources.