CSE 5544
Transcript Abbreviation:
Intr Data Vis
Course Description:
Principles and methods for visualizing data from measurements and calculations in physical and life sciences, and transactional and social disciplines; information visualization; scientific visualization.
Course Levels:
Undergraduate (1000-5000 level)
Graduate (5000-8000 level)
Designation:
Elective
General Education Course:
(N/A)
Cross-Listings:
(N/A)
Credit Hours (Minimum if “Range”selected):
3.00
Max Credit Hours:
(N/A)
Select if Repeatable:
Off
Maximum Repeatable Credits:
(N/A)
Total Completions Allowed:
(N/A)
Allow Multiple Enrollments in Term:
No
Course Length:
14 weeks (autumn or spring)
12 weeks (summer only)
Off Campus:
Never
Campus Location:
Columbus
Instruction Modes:
In Person (75-100% campus; 0-24% online)
Prerequisites and Co-requisites:
Prereq: 5361, Stat 3301, 3541, or 5541.
Electronically Enforced:
No
Exclusions:
Not open to students with credit for 694L.
Course Goals / Objectives:
Be competent with design principles of creating viable visualizations
Be competent with visualization algorithms and data structures
Be competent with creation of interactive visualizations
Be competent with the collection and processing of diverse collections of data
Be competent with including perceptual considerations into visualization systems
Be familiar with with practical applications of visualization
Be familiar with visualization needs of domains from science, medicine, and commerce
Be familiar with the critiques of visualization systems
Be familiar with gaining insights into visualization problems and phenomenon
Check if concurrence sought:
No
Contact Hours:
| Topic | LEC | REC out-of-class | REC in-class | Weekly LAB out-of-class | Weekly LAB in-class |
|---|---|---|---|---|---|
| Historical remarks | 1.0 | 0.0 | 0 | 0.0 | 0 |
| Abstract visualization concepts and the visualization pipeline | 1.0 | 0.0 | 0 | 0.0 | 0 |
| Data acquisition and representation | 2.0 | 0.0 | 0 | 0.0 | 0 |
| Principles of visual design | 2.0 | 0.0 | 0 | 0.0 | 0 |
| Basic mapping concepts | 1.0 | 0.0 | 0 | 0.0 | 0 |
| Focus+context, and navigation+zoom | 1.0 | 0.0 | 0 | 0.0 | 0 |
| Perception and color theory | 4.0 | 0.0 | 0 | 0.0 | 0 |
| Case study: trends application | 1.0 | 0.0 | 0 | 0.0 | 0 |
| Visualization of matrices, graphs and trees | 3.0 | 0.0 | 0 | 0.0 | 0 |
| Visualization of high-dimensional data and dimensionality reduction techniques | 5.0 | 0.0 | 0 | 0.0 | 0 |
| Case study: bioinformatics | 3.0 | 0.0 | 0 | 0.0 | 0 |
| Visualization of scalar fields (color maps, isosurface extraction, volume rendering) | 3.0 | 0.0 | 0 | 0.0 | 0 |
| Case study: medical and biological imaging | 3.0 | 0.0 | 0 | 0.0 | 0 |
| Visualization of vector fields (particle tracing, texture-based methods, vector field topology) | 3.0 | 0.0 | 0 | 0.0 | 0 |
| Case study: flow visualizations | 1.0 | 0.0 | 0 | 0.0 | 0 |
| Evaluation and Interaction models | 2.0 | 0.0 | 0 | 0.0 | 0 |
| Visualization of Large data | 1.0 | 0.0 | 0 | 0.0 | 0 |
| Visualization of spatio-temporal data | 2.0 | 0.0 | 0 | 0.0 | 0 |
| Final Presentations | 1.0 | 0.0 | 0 | 0.0 | 0 |
| Total | 40 | 0 | 0 | 0 | 0 |
Grading Plan:
Letter Grade
Course Components:
Lecture
Grade Roster Component:
Lecture
Credit by Exam (EM):
No
Grades Breakdown:
| Aspect | Percent |
|---|---|
| Laboratory assignments | 40% |
| Midterm exam | 20% |
| Final exam and/or projects | 30% |
| Class participation | 10% |
Representative Textbooks and Other Course Materials:
| Title | Author | Year |
|---|---|---|
| Visual Thinking for Design | Colin Ware | |
| Visualizing Data | Ben Fry |
ABET-CAC Criterion 3 Outcomes:
| Substantial contribution (3-6 hours) | 1 | Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions. |
| Substantial contribution (3-6 hours) | 2 | Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline. |
| Significant contribution (7+ hours) | 3 | Communicate effectively in a variety of professional contexts. |
| Substantial contribution (3-6 hours) | 4 | Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles |
| Substantial contribution (3-6 hours) | 5 | Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline |
| Some contribution (1-2 hours) | 6 | Apply computer science theory and software development fundamentals to produce computing-based solutions. |
ABET-ETAC Criterion 3 Outcomes:
(N/A)
ABET-EAC Criterion 3 Outcomes:
| Substantial contribution (3-6 hours) | 1 | an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics |
| Substantial contribution (3-6 hours) | 2 | an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors |
| Significant contribution (7+ hours) | 3 | an ability to communicate effectively with a range of audiences - pre-2019 EAC SLO (g) |
| Substantial contribution (3-6 hours) | 4 | an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts |
| Substantial contribution (3-6 hours) | 5 | an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives |
| Significant contribution (7+ hours) | 6 | an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions |
| Substantial contribution (3-6 hours) | 7 | an ability to acquire and apply new knowledge as needed, using appropriate learning strategies |
Embedded Literacies Info: