Instructor: Prof. Tommy Dang (Tuan Dang)
Email: tommy.dang@ttu.edu
Office hours: 2:00 pm - 2:45 pm MWF and available to talk right after the class
Office: EC 306J

Class: EC110, 3:00 pm - 3:50 pm MWF Aug 29, 2016 - Dec 14, 2016
Undergraduate level: Special Topics in Computer Science: Visualization and Visual Analytics - 38041 - CS 4331 - 004
Graduate level: Special Problems in Computer Science: Visualization and Visual Analytics - 38042 - CS 5331 - 004

Tutarioal Assistant (TA): Judas Tadeo (JT)
Email: judas.tadeo@ttu.edu
Office hours: 11:30 am - 1:00pm, Eng Center 202
Course Description:
  • This course introduces material on designing effective visualizations. This course is going to focus on the basics of visualization, covering principles, methods, and techniques that are foundational to both information and scientific visualization.
  • During the course, students will get hands-on experiences on building interactive visualizations for various real-world datasets. Students will be accessed their learnings through three visualization projects.
  • Extensive computer use is required.
    • Prerequisites:
  • Students are expected to have basic programming skills. Completed material in computer programming topics (e.g. CS 2413: Data Structures, CS 3364: Design & Analysis of Algorithms or equivalent) is helpful but not required.
  • Students majoring in areas other than Computer Science are also encouraged to enroll.
  • Please contact the instructor if you are unsure if you satisfy the prerequisites.
    • Attendance:
    Attendance is not mandatory. However, part of your grade is from your in-class participation/contribution. So, you should consider to go the all classes, make comments on other people's work, ask questions, and ask good questions.
    Class policies:
  • No cell phone usage and no eating during class.
  • Academic dishonesty, such as cheating or plagiarism, is a serious offense. For the class projects, you are expected to come up with your own design ideas and implement your work. If you are caught cheating, the grade of F will stand as your final grade (see Part II B 2 of the Student Handbook). The instructor may recommend to Student Judicial Programs for more serious/repeated violations. (OP 34.12)
  • Any student who, because of a disability, may require special arrangements in order to meet the course requirements should contact the instructor as soon as possible to make any necessary arrangements. (OP 34.22)
  • A student who intends to observe a religious holy day should make that intention known in writing to the instructor prior to the absence. (OP 34.19)
    • Evaluation:
    The numeric breakdown of your final grade is computed as follows::
    Percentage What to do Notes
    Project 1: 20% Time series visualization Individual project
    Project 2: 30% Geospatial visualization Group project (teammates are assigned by instructor)
    Project 3: 30% Network visualization Group project (teammates are selected by students)
    Peer evaluation: 10% Feeback from teammates for Project 2 and 3
    Class Participation: 10% Comments/Ask questions if you are a distant student, this 10% will go to your Project 1

      A = 85 - 100%
      B = 70 - 84%
      C = 55 - 69%
      D = 40 - 54%
      F = 0 - 39%
    Schedule:
    Topics
    Week 1: 8/29 - 9/2 - Course overview
    - Project 1 is out
    Week 2: 9/5 - 9/9 - Introduction to Javascript
    Week 3: 9/12 - 9/16 - Introduction to D3.js
    Week 4: 9/19 - 9/23 - Introduction to Visualization
    - Information Visualization vs. Visual Analytics
    Week 5: 9/26 - 9/30 - Tables and Charts
    - Scatterplots and Paralell Coordinates
    Week 6: 10/3 - 10/7 - Text visualization
    - Project 1 is due at 11:59pm Sunday, 10/2
    Week 7: 10/10 - 10/14 - Project 1 presentations
    - Project 2 is out => Team assigment
    Week 8: 10/17 - 10/21 - Arcs diagrams
    - Geospatial Visualization
    Week 9: 10/24 - 10/28 - Tree layouts
    - Hierarchical edge bundling
    Week 10: 10/31 - 11/4 - Project 2 is due at 11:59pm Sunday, 11/6
    Week 11: 11/7 - 11/11 - Project 2 presentations
    Week 12: 11/14 - 11/18 - Project 3 is out => Team formation
    - Network visualization
    Week 13: 11/21 - 11/25 - Adjacency matrices
    - Force-directed layout in D3
    Week 14: 11/28 - 12/02 - Dynamic network visualization
    - Visualizing Uncertainty in networks
    Week 15: 12/05 - 12/09 - Project 3 is due at 11:59pm Sunday, 12/11
    Week 16: 12/12 - 12/16 - Project 3 presentations
    Textbooks:

    Visualization Analysis and Design

    by Tamara Munzner

    CRC Press, 2014
    ISBN: 978-1466508910
    $75 hardcover
    Interactive Data Visualization for the Web

    by Scott Murray

    O'Reilly, 2013
    ISBNL 978-1449339739
    available for free online
    © Last revised: Sep 6th, 2016