605.662.81 - Data Visualization

Expanded Course Description

As organization and individuals continue to rely more in data to make informed decisions, there has been an interested in studying effective ways to explore the information.  Data visualization is a research area that focuses on the use of visualization techniques to help people understand and analyze data. When well-designed visualization tools are provided to users, they can take advantage of the powerful human cognitive capabilities and improve comprehension, memory, and inference. This multidisciplinary course introduces the practical concepts of graphic design related to data visualization and interactive design.   This course explores the underlying theory and practical concepts in creating visual representations of heterogeneous data.  It covers the core topics in data visualization including data representation, design principles, color, interaction, network visualization, cartography, volume rendering, and visual analytics.

Course Structure

The course materials are divided into modules which can be accessed by clicking Course Modules on the left menu. A module will have several sections including the overview, lectures and content, readings, discussions, and assignments. You are encouraged to preview all sections of the module before starting. Modules run for a period of seven (7) days, any exceptions are noted on the Course Outline page. You should regularly check the Calendar and Announcements for assignment due dates.

Course Topics

Introduction to Data Visualization

Introduction to Visualization Techniques

Human Visual Perception

Visualization Design Principles

Color in Visualization

Interactive Visualization

Trees, Graphs, and Network Visualization

Maps and Cartography Visualization

Text Visualization

Temporal Visualization

Scientific Visualization

Isosurfaces and Flow Visualization

Display Systems and Evaluation

Course Goals

To learn practical concepts of graphic design related to data visualization and interactive design.  This course will explore the underlying theory and practical concepts in creating visual representations of heterogeneous data.  It will cover the core topics in data visualization including data representation, design principles, color, interaction, network visualization, cartography, volume rendering, and visual analytics. The new knowledge acquired during the semester will be used to solve practical data visualization and visual analytics problems.

Course Learning Outcomes (CLOs)

• Describe the foundations of the human visual perception and how it relates to creating effective information visualizations.
• Understand the design principles for creating effective visualization tools
• Evaluate different visualization techniques and identify potential misleading charts and visualizations
• Demonstrate familiarity of the visual design process by developing interactive data visualization tools
• Understand different data types including tabular, hierarchical, geospatial, textual, and scalar and related visualization techniques to each data type

Textbooks

Not required.

Required Software

During the semester student might be asked to download software applications like Tableau, PowerBI, Qlik, Python, R, R Studio, and/or Paraview.

Student Coursework Requirements

It is expected that each module will take approximately 7–10 hours per week to complete. Here is an approximate breakdown: video lectures and reviewing corresponding slides (approximately 2-3 hours per week), reading the assigned sections of the texts (approximately 2-3 hours per week) as well as some outside reading, writing programming assignments (approximately 2–3 hours per week), and online discussion (approximately 1 hour per week).

This course will consist of three basic student requirements.

1. Participation (20% of Final Grade Calculation)

Participation will be graded based on weekly discussions.  Most of the discussion of the class will happen online at the discussion board.  Each module will have a topic / question that students must answer to obtain credit. To enable student interaction, students will be also required to reply to at least one comment from another student.  To receive credit, the discussion of a specific module must happen before the first day of the following module.

2. Course Projects (50% of Final Grade Calculation)

Projects will count for 50% of the final grade.  They will be distributed throughout the semester to enable students a hands-on experience of implementing visualization techniques to explore data.  Students will write papers or user Python, R, Tableau and/or other tools to implement programming assignments associated with some projects.   Projects will be graded according to (a) the quality of the results and (b) the clarity of the program or source code.  See generic rubric below that will be used to grade programming assignments.

3. Final Project (30% of Final Grade Calculation)

The final project is a significant part of the course. It allows students to synthesize the concepts learned throughout the semester and apply them to their own images and/or to their particular area of interest.  The final project grades will be based on the following components:

• Draft Proposal (10%)
• Revised Proposal (10%)
• Literature survey (10%)
• Final video submission (20%)
• Final Project (Paper, Program, Code, etc...) (50%)
  

Grading Policy

The course will consist of 14 modules.  Each module will include a video lecture, corresponding slides, reading assignment, and an online discussion. The grading of this course will be based on:

Projects are due according to the dates posted in your Blackboard course site. You may check these due dates in the Course Calendar or the Assignments in the corresponding modules. I will post grades 1-2 weeks after assignment due dates.  The code (if any) for your programming assignments must be submitted and should include enough documentation so we can read your code and understand the approach you are following.  

In written sections and the final paper, we generally do not directly grade spelling and grammar. However, egregious violations of the rules of the English language will be noted without comment. Consistently poor performance in either spelling or grammar is taken as an indication of poor written communication ability that may detract from your grade.

Final grades will be assigned according to the following scale:

100–98 = A+
97–94 = A
93–90 = A−
89–87 = B+
86–83 = B
82–80 = B−
79–70 = C
<70 = F

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.