Data Visualization - School of Interdisciplinary Arts & Sciences (2024)

On this page: Major Description | Requirements | Learning Objectives | | Courses

Students in the Data Visualization major will enter the workforce with the ability to identify trends, provide insights, and illustrate the societal impacts of different forms of data while critically engaging with data visualization software and programming languages. Data Visualization emphasizes fundamental elements of database management, data analysis and visualization, information systems, and quantitative and qualitative analysis.

Offering both a Bachelor of Arts and a Bachelor of Science in Data Visualization beginning Autumn 2024 Quarter. Completed the prerequisite courses? Current UW Bothell Pre-Major students can submit a declaration form, follow this link to theIAS Major Declaration Form.

DEGREE OPTIONS

BACHELOR OF ART

A student with a Bachelor of Arts (BA) in Data Visualization may enter the variety of academic and career fields focused on data analysis and visualization, including statistics, visual analytics, and geographic information systems and sciences. A Bachelor of Arts in Data Visualization emphasizes fundamental elements of database management, data analysis and visualization, information systems, and quantitative and qualitative analysis.

BACHELOR OF SCIENCE

A student with a Bachelor of Science (BS) in Data Visualization will enter into the wide variety of academic and career fields focused on data analysis and visualization, including statistics, visual analytics, and geographic information systems and sciences. A Bachelor of Science in Data Visualization degree emphasizes fundamental elements of data science, visualization, and analytics, advanced research, advanced graduate programs, or other data programing and geographic information systems and sciences programs and careers.

Learning objectives

The Data Visualization Curriculum advances the five core IAS learning objectives. Students taking courses and/or majoring in Data Visualization:

1. Acquire critical competence in different ways to address real-world, quantitative concerns and to find solutions that are both efficient and equitable.
2. Learn to apply statistical and mathematical tools and critique their applications, including building and evaluating arguments based on quantitative data.
3. Generate reliable data and choose appropriate methods to apply to a given data set.
4. Gain experience creating visual representations of problems and data, and communicate these ideas, results, and analyses in multiple formats.
5. Learn to work in interdisciplinary teams to communicate and to understand a range of issues, especially those around social and planetary justice, that have quantitative underpinnings.
6. Synthesize quantitative research with other ways of knowing.

Recommended preparation

Interested in exploring this major but not ready to commit? Consider taking one of the below courses! Any of these selections will help familiarize you with the academic program and prepare you for advanced coursework in the major.

• BIS 111/CSS 101 Digital Thinking
• BIS 115 Digital Cultures
• BIS 140 Numbers in News Media
• BIS 215 Understanding Statistics
• BIS 232 Introduction to Data Visualization
• B DATA 200 Introduction to Data Studies
• CSS 107 Introduction to Programming through Animated Storytelling
• CSS 112 Introduction to Programming for Scientific Applications

Degree prerequisites

Bachelor of Arts Prerequisites

• English Composition Coursework (10 credits)
  • B WRIT 133 or B WRIT 134 or ENGL 131 or equivalent Composition Course
  • B WRIT 135 or ENGL 141 or equivalent Composition course
• Statistics Coursework (5 credits)
  • BIS 215 Understanding Statistics or B MATH 215 Health Statistics or B BUS 215 Business Statistics or STAT 220 Statistical Reasoning or equivalent introduction to statistics course
• Pre-Calculus Coursework
  • B MATH 123 Precalculus II or MATH 120 Precalculus or minimum score of 400 on the MTHDSP

Bachelor of Science Prerequisites

• English Composition Coursework (5 credits)
  • B WRIT 133 or B WRIT 134 or ENGL 131 or equivalent Composition Course
• Statistics Coursework (5 credits)
  • BIS 215 Understanding Statistics or B MATH 215 Health Statistics or B BUS 215 Business Statistics or STAT 220 Statistical Reasoning or equivalent introduction to statistics course
• Calculus Coursework (5 credits)
  • STMATH 124 Calculus 1 or MATH 124 Calculus 1
• Computer Programming Coursework (10 credits)
  • CSS 142 Computer Programming I or CSE 142 Computer Programming I or CSE 122 Intro to Computer Programming II
  • CSS 143 Computer Programming II or CSE 143 Computer Programming II or CSE 123 Intro to Computer Programming III

Degree requirements

Bachelor of Arts Degree Requirements

• Data Visualization Core Courses
  • B DATA 200 Introduction to Data Studies (5 credits)
  • BIS 232 Introduction to Data Visualization (5 credits)
  • Either BIS 218 Power of Maps OR BIS 342 Geographic Information Systems (5 credits)
  • Either BES 301 Science Methods and Practice OR BST 301 Scientific Writing (5 credits)
• Advanced Data Visualization and Analysis Methods (15 Credits)
• Spatial Data Analysis (15 credits)
• Data Visualization Electives (25 credits)

Bachelor of Arts- 75 credits total

Bachelor of Science Degree Requirements

• Data Visualization Core Courses
  • B DATA 200 Introduction to Data Studies (5 credits)
  • BIS 232 Introduction to Data Visualization (5 credits)
  • Either BIS 218 Power of Maps OR BIS 342 Geographic Information Systems (5 credits)
  • Either BES 301 Science Methods and Practice OR BST 301 Scientific Writing (5 credits)
  • Either STMATH 125 or MATH 125 Calculus 2 (5 credits)
  • Either STMATH 126 or MATH 126 Calculus 3 (5 credits)
  • Either BIS 231 Linear Algebra or STMATH 208 Matrix Algebra (5 credits)
• Advanced Data Visualization and Analysis Methods (15 Credits)
• Spatial Data Analysis (15 credits)
• Data Visualization Electives (25 credits)

Bachelor of Science- 90 credits total

School of IAS Requirements and Policies

• Residency Requirement: 30 credits must be completed in residency at UW Bothell
• Cumulative GPA Requirement: Major GPA must be at a cumulative of 2.00 or higher
• Interdisciplinary Practice & Reflection (IPR): The IPR requirement can be completed through elective credits or it can overlap with major coursework. Please see the IPR website for course options
• Upper Division Credit Policy: Of the credits applying to the Data Visualization major requirements, a minimum of 45 credits must be completed at the Upper Division (300-400) level

People

Faculty

• Joe FerrareFaculty Coordinator
• Baska Anderson
• Carrie Bodle
• Shauna Carlisle
• Charlie Collins
• Colin Danby
• Cinnamon Hillyard
• Jin-Kyu Jung
• Santiago Lopez
• Sara Maxwell
• Rebecca Price
• Caleb Trujillo
• Rob Turner

Academic Advisor

• Nhi Tran

Research Librarian

• Alyssa Berger

Courses

A. Core Courses

• B DATA 200 Introduction to Data Studies (5 credits)
• BIS 232 Introduction to Data Visualization (5 credits)
• Either BIS 218 Power of Maps OR BIS 342 Geographic Information Systems (5 credits)
• Either BES 301 Science Methods and Practice OR BST 301 Scientific Writing (5 credits)
• Additional Bachelor of Science Core Courses:
  • Either STMATH 125 or MATH 125 Calculus 2 (5 credits)
  • Either STMATH 126 or MATH 126 Calculus 3 (5 credits)
  • Either BIS 231 Linear Algebra or STMATH 208 Matrix Algebra (5 credits).

B. Advanced Data Visualization and Analysis Methods Courses (15 credits)

• BIS 411 Network Analysis & Visualization (5 credits)
• BIS 412 Advanced Data Visualization (5 credits)
• BIS 447 Topics in Quantitative Inquiry (5 credits)
• BISMCS 473 Visual Communication (5 credits)
• B BUS 301 Data Management (5 credits)

C. Spatial Data Analysis Courses (15 credits)

• BIS 343 Geovisualization (5 credits)
• BIS 344 Intermediate Geographic Information Systems (5 credits)
• BIS 352 Mapping Communities (5 credits)
• BIS 442 Advanced Geographic Information Systems (5 credits)
• BES 303 Environmental Monitoring Practicum (5 credits)
• BES 440 Remote Sensing of the Environment (5 credits)

D. Data Visualization Elective Courses (25 credits)

• Bachelor of Science, Elective Courses
  • BIS 111/CSS 101 Digital Thinking (5 credits)
  • BIS 115 Digital Cultures (5 credits)
  • BIS 140 Numbers in News Media (5 credits)
  • BIS 218 Power of Maps (5 credits)
  • BIS 235 Critical Media Literacy (5 credits)
  • BIS 236 Introduction to Interactive Media (5 credits)
  • BIS 331 Journal and Media History (5 credits)
  • BIS 312 Approaches to Social Research Methods (5 credits)
  • BIS 332 Digital Global Industries (5 credits)
  • BIS 340 Approaches to Cultural Research Methods (5 credits)
  • BIS 342 Geographic Information Systems (5 credits)
  • BIS 372 Representation, Colonialism, and the Tropical World (5 credits)
  • BIS 380 Bioethics (5 credits)
  • BIS 382 the Visual Art of Biology (5 credits)
  • BIS 406 Urban Planning and Geography (5 credits)
  • BIS 410 Topics in Qualitative Inquiry (5 credits)
  • BIS 421 Technology Policy (5 credits)
  • BEARTH 201 Mapping the Earth System (5 credits)
  • BEARTH 202 Modeling Global Systems (5 credits)
  • BISIA 244 Time-Based Media Art
  • BISIA 250 Photography as Art
  • BISIA 344 Video Art (5 credits)
  • BISIA 350 Photography and Digital Art (5 credits)
  • BISIA 444 Video Installation Art (5 credits)
  • BISIA 450 Image and Imagination (5 credits)
  • BISLEP 302 Policy Analysis (5 credits)
  • BISSTS 307 Science, Technology, and Society (5 credits)
  • BISSTS 355 History of Science and Technology (5 credits)
  • CSS 211 Computers and Society
  • CSS 342 Data Structures, Algorithms, and Discrete Mathematics I
  • CSS 343 Data Structures, Algorithms, and Discrete Mathematics II
  • CSS 385 Introduction to Game Development
  • CSS 411 Computing Technology and Policy
  • STMATH 300 Foundations of Modern Math
  • STMATH 341 Introduction to Statistical Inference
  • B IMD 233 Fundamentals of Web Media Technology (5 credits)
  • B IMD 250 Introduction to Interaction Design (5 credits)
• Bachelor of Arts, Elective Courses
  • In addition to the Bachelor of Science electives listed above, Bachelor of Arts students can take:
  • BIS 231 Linear Algebra (5 credits)
  • CSS 110 Intro to Cybersecurity
  • CSS 112 Introduction to Programming for Scientific Application
  • CSS 123 Programming for Data Science
  • CSS 142 Computer Programming I
  • CSS 143 Computer Programming II
  • B MATH 144 Calculus for the Life Sciences
  • STMATH 124 Calculus I
  • STMATH 125 Calculus II
  • STMATH 126 Calculus III
  • STMATH 208 Matrix Algebra

Looking to fulfill a requirement?