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Kalina Borkiewicz and AJ Christensen

This course is an introduction to 3D scientific data visualization, with an emphasis on science communication and cinematic design for appealing to broad audiences. You will develop visualization literacy, through being able to interpret/analyze (read) visualizations and create (write) your own visualizations.

By the end of this course, you will:

-Develop visualization literacy.

-Learn the practicality of working with spatial data.

-Understand what makes a scientific visualization meaningful.

-Learn how to create educational visualizations that maintain scientific accuracy.

Read more

This course is an introduction to 3D scientific data visualization, with an emphasis on science communication and cinematic design for appealing to broad audiences. You will develop visualization literacy, through being able to interpret/analyze (read) visualizations and create (write) your own visualizations.

By the end of this course, you will:

-Develop visualization literacy.

-Learn the practicality of working with spatial data.

-Understand what makes a scientific visualization meaningful.

-Learn how to create educational visualizations that maintain scientific accuracy.

-Understand what makes a scientific visualization cinematic.

-Learn how to create visualizations that appeal to broad audiences.

-Learn how to work with image-making software. (for those completing the Honors track)

Enroll now

What's inside

Syllabus

Course Orientation
You will become familiar with the course, your classmates, and our learning environment.
Week 1: Introduction
Week 1 is an introduction to the field of data visualization, as well as related fields like computational science and computer graphics. You will learn about different types of data visualization, and visualization best practices.
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Week 2: Data
Week 2 is all about data - how are spatial data represented in a computer? How is it formatted? Where can you find it, and how do you work with it?
Week 3: Meaningful Communication
Week 3 is all about the human side of things. How do people learn? How do we perceive visual information? What makes certain methods of communication and education more effective? How do you find a story in a dataset, and how do you tell that story clearly and concisely?
Week 4: Cinematic Presentation
Week 4 is about presenting your visualization in an engaging way to broad audiences with techniques like camera design, lighting, compositing, digital cosmetics, and other tricks from Hollywood. You’ll also learn how to package your visualization with sound, titles, and credits, and you’ll learn how to distribute it to various types of audiences.
Conclusion
Congratulations on reaching the end of the course!

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Meets a standard quantity of course objectives that are typical to introductory topics
Develops visualization literacy, which is helpful for broad audiences
Develops visualization skills beyond literacy, which is helpful for certain learners
Teaches how to create educational visualizations while maintaining scientific accuracy, which is useful for a range of industries
Taught by Kalina Borkiewicz and AJ Christensen, who are experts in the field of 3D scientific data visualization
Provides opportunities for learners to work with image-making software in the Honors track of the course

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Reviews summary

In-depth science visualization course

Learners say that this course is especially in-depth, but some reviewers express concerns about its fast pace. Additionally, the course covers advanced visualization concepts that many students find helpful.
This course teaches students advanced concepts in science visualization.
"Mucho de lo que no se ve dentro del desarrollo de visualizaciones es explicado de una manera excepcional en el curso."
The course moves at a fast pace.
"sometimes I felt like too many information were provided in a very restricted timescale."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in 3D Data Visualization for Science Communication with these activities:
Compile: Course Materials
Stay organized and prepare for the course by compiling all necessary materials in one place.
Show steps
  • Create a digital or physical folder for the course.
  • Download and save all course materials, including notes, assignments, and quizzes.
  • Organize the materials logically and label them clearly.
Refresh: Python Programming
Ensure a strong foundation in Python programming before the course begins.
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  • Review the basics of Python programming.
  • Complete a few practice problems or coding exercises.
Tutorial: Blender's Interface
Familiarize yourself with Blender's interface before the course begins to get a running start on learning to create visualizations.
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  • Watch at least one tutorial video on Blender's interface.
  • If something is unclear, refer to the Blender documentation for clarification.
18 other activities
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Practice: Manipulating Objects in Blender
Get comfortable navigating and manipulating objects in Blender before the course begins.
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Show steps
  • Follow along with a tutorial on basic object manipulation in Blender.
  • Download a sample 3D model and import it into Blender.
  • Use the Transform tools to move, rotate, and scale the object.
Review Data Visualization Fundamentals
Reviewing data visualization fundamentals will strengthen your understanding of the basic principles and concepts used throughout the course.
Show steps
  • Read through introductory articles and tutorials on data visualization.
  • Review examples of effective and ineffective data visualizations.
  • Complete practice exercises or quizzes on data visualization concepts.
Read: The Data Visualization Handbook
Prepare for the course by reading this introductory book on data visualization theory and practices.
Show steps
  • Read and take notes on the first three chapters of the book.
  • Complete any exercises or activities in the book.
Explore online resources and tutorials for 3D data visualization
Supplement your learning with additional resources and expert guidance
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Show steps
  • Identify reputable websites, blogs, or online courses that provide tutorials on 3D data visualization
  • Choose tutorials that align with your learning objectives and skill level
  • Follow the tutorials, complete exercises, and apply what you learn to your own projects
Follow a tutorial series on basic data visualization
Solidify the foundational concepts and techniques in data visualization.
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Show steps
  • Identify a reputable tutorial series on data visualization.
  • Set aside dedicated time to follow the tutorials.
  • Take notes and practice the techniques.
  • Apply what you learn to analyze and visualize small datasets.
Follow Tutorials on Visualization Tools
By following tutorials on visualization tools, you'll gain practical experience using the software used in the course.
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Show steps
  • Choose a visualization tool relevant to the course, such as Blender or ParaView.
  • Find tutorials for beginners covering the basics of the tool.
  • Complete the tutorials to learn how to import, manipulate, and visualize data.
Participate in Peer Review Sessions
Participating in peer review sessions will allow you to receive feedback on your data visualization work and learn from others.
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Show steps
  • Find a peer or group of peers interested in data visualization.
  • Share your visualizations with each other and provide constructive feedback.
  • Incorporate feedback to improve your visualizations and enhance your understanding.
Practice creating visualizations using image-making software
Enhance your skills in creating visualizations using industry-standard software
Show steps
  • Find or create a dataset that you can use to practice your visualization skills
  • Choose an image-making software and complete tutorials to learn its basic features
  • Use the software to create several different visualizations of your dataset
Practice creating visualizations in different formats
Develop proficiency in using data visualization tools and techniques to create informative and engaging visualizations.
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Show steps
  • Choose a variety of datasets to work with.
  • Use different visualization tools to create various chart types.
  • Experiment with different design elements and color schemes.
Interpret and Critique Data Visualizations
Practicing the interpretation of data visualizations will enhance your ability to analyze and communicate scientific findings effectively.
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Show steps
  • Gather a variety of data visualizations, such as charts, graphs, and infographics.
  • Analyze each visualization, identifying the type of data being presented and the key insights conveyed.
  • Write down your interpretations and critique the effectiveness of the visualizations.
Attend workshops or conferences related to 3D data visualization
Connect with experts, learn about industry trends, and gain practical experience
Show steps
  • Research upcoming workshops or conferences on 3D data visualization
  • Attend sessions, participate in discussions, and network with other attendees
  • Apply what you learn to your own projects or research
Workshop: Data Visualization with D3.js
Deepen your understanding of data visualization by attending a workshop on a specific tool or technique.
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Show steps
  • Research and find a data visualization workshop that is relevant to the course.
  • Register for the workshop and attend all sessions.
  • Take notes and complete any exercises or activities during the workshop.
  • Reach out to the workshop instructor with any questions or for further guidance.
Develop a Data Visualization Storyboard
Creating a storyboard will help you plan and structure your data visualization to make it both informative and visually engaging.
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Show steps
  • Define the goal and target audience for your data visualization.
  • Brainstorm ideas for the visualization, including the type of data, visual elements, and narrative.
  • Create a storyboard outlining the sequence of scenes and transitions in your visualization.
Develop a visualization portfolio
Showcase your visualization skills and enhance your employability in the field
Show steps
  • Gather your best visualizations and organize them into a portfolio
  • Write descriptions for each visualization, explaining the dataset, the techniques you used, and the insights you gained
  • Consider creating a website or online gallery to host your portfolio
Peer Session: Collaborative Visualization Project
Reinforce your knowledge and skills by collaborating with peers on a visualization project.
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Show steps
  • Find a partner or group to work with.
  • Choose a dataset that you are interested in visualizing together.
  • Decide on the best way to visualize the data and create a plan.
  • Work together to create your visualization.
  • Present your visualization to the class.
Build a Data Visualization Project
Engaging in a data visualization project will provide hands-on experience in applying the concepts and techniques learned in the course.
Show steps
  • Choose a dataset that aligns with your interests or field of study.
  • Define the research question or hypothesis you want to explore.
  • Design and create visualizations to communicate your findings effectively.
Mentor a junior student or provide support in an online community
Solidify your knowledge by teaching others and contribute to the community
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Show steps
  • Identify a junior student who is interested in learning about 3D data visualization
  • Share your knowledge, provide guidance, and answer their questions
  • Participate in online forums or communities and provide support to other learners
Project: Create a Scientific Visualization
Apply what you have learned in the course by creating your own scientific visualization.
Show steps
  • Choose a dataset that you are interested in.
  • Load the dataset into Python or another data visualization software.
  • Explore the data and decide on the best way to visualize it.
  • Create a prototype of your visualization.
  • Get feedback on your prototype and make improvements.
  • Create your final visualization.

Career center

Learners who complete 3D Data Visualization for Science Communication will develop knowledge and skills that may be useful to these careers:
Science Communicator
Science Communicators translate complex scientific concepts into clear and engaging content for the general public. This course can help you develop the skills needed to create effective and accessible science communication materials, such as articles, videos, and presentations.
Data Journalist
Data Journalists investigate and report on stories using data. This course can help you develop the skills needed to gather, analyze, and visualize data to create compelling and informative stories.
Technical Writer
Technical Writers craft instruction manuals and other explanatory documents for a wide range of technical products and services. This course can help you to develop the skills needed to produce accurate and engaging documentation for scientific software and tools.
Interactive Developer
Interactive Developers design and develop interactive web applications and other digital products. This course can help you develop the skills needed to create interactive scientific visualizations and simulations.
Multimedia Producer
Multimedia Producers plan, direct, and coordinate the production of multimedia projects, such as videos, podcasts, and interactive presentations. This course can help you develop the skills needed to produce engaging and effective multimedia content for scientific communication.
Museum Educator
Museum Educators develop and deliver educational programs at museums and other cultural institutions. This course can help you develop the skills needed to create and deliver engaging and informative museum exhibits and programs.
Science Educator
Science Educators develop and deliver educational programs that teach science to students of all ages. This course can help you develop the skills needed to create and deliver effective science lessons and activities.
Science Policy Analyst
Science Policy Analysts research and analyze scientific and technical issues to inform policy decisions. This course can help you develop the skills needed to evaluate scientific evidence and communicate complex scientific concepts to policymakers.
Visual Designer
Visual Designers create visual concepts, using computer software or by hand, to communicate ideas that inspire, inform, and captivate consumers. This course can help you develop the skills needed to create visually appealing and effective scientific visualizations.
Grant Writer
Grant Writers develop and submit grant proposals to secure funding for research and other projects. This course can help you develop the skills needed to write compelling and persuasive grant proposals for scientific research.
Public Relations (PR) Specialist
Public Relations (PR) Specialists manage the public image of organizations and individuals. This course can help you develop the skills needed to create and manage effective PR campaigns for scientific organizations and initiatives.
Information Architect
Information Architects design and organize the structure and content of websites, intranets, online communities, and software applications. This course can help you develop the skills needed to create effective and user-friendly information architectures for scientific websites and applications.
Digital Marketer
Digital Marketers develop and execute marketing campaigns that use digital channels, such as social media, search engines, and email. This course can help you develop the skills needed to create and manage effective digital marketing campaigns for scientific products and services.
User Experience (UX) Designer
User Experience (UX) Designers research, design, and evaluate the user experience of products and services. This course can help you develop the skills needed to design and evaluate user interfaces for scientific software and tools.
Science Librarian
Science Librarians help scientists and other researchers find and access the information they need. This course can help you develop the skills needed to manage and provide access to scientific information.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in 3D Data Visualization for Science Communication.
This classic book on data visualization must-read for anyone who wants to learn about the principles of effective visual communication. It covers a wide range of topics, from the design of charts and graphs to the use of color and typography.
This practical guide to data storytelling valuable resource for anyone who wants to learn how to communicate data effectively to a wide audience. It covers a range of topics, from data collection and analysis to the design of presentations and reports.
Provides a comprehensive introduction to data visualization, covering the principles of visual perception, data encoding, and interaction design. It valuable resource for students and practitioners who want to learn the fundamentals of data visualization.
This classic book on typography must-read for anyone who wants to learn about the principles of effective typography. It covers a wide range of topics, from the choice of typefaces to the layout of text.
Provides a comprehensive introduction to interactive data visualization for the web, covering the principles of data visualization, web development, and user experience design. It valuable resource for students and practitioners who want to learn how to create effective interactive data visualizations for the web.
Provides a practical guide to data science, covering the principles of data analysis, machine learning, and ethics. It valuable resource for students and practitioners who want to learn how to use data science to solve real-world problems.
Provides a comprehensive introduction to machine learning, covering the principles of data analysis, machine learning algorithms, and deep learning. It valuable resource for students and practitioners who want to learn how to use machine learning to solve real-world problems.
Provides a comprehensive introduction to deep learning for natural language processing, covering the principles of deep learning, natural language processing, and applications. It valuable resource for students and practitioners who want to learn how to use deep learning to solve real-world problems in natural language processing.
Provides a comprehensive introduction to TensorFlow, a popular deep learning library. It covers the principles of deep learning, TensorFlow, and applications. It valuable resource for students and practitioners who want to learn how to use TensorFlow to solve real-world problems.
Provides a comprehensive introduction to motion graphics, covering the principles of animation, typography, and sound design. It valuable resource for students and practitioners who want to learn how to create engaging and effective motion graphics.
Provides a comprehensive introduction to visual thinking, covering the principles of perception, cognition, and communication. It valuable resource for students and practitioners who want to learn how to use visual thinking to solve problems and communicate ideas.

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