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Data-Driven Information Visualization

Data-Driven Information Visualization


Data-Driven Information Visualization

About this course

Visual information displays have epic significance for communicating knowledge. The world is complex, diverse, and always changing, but our screens are mostly flat and paper prints are static. When we succeed at displaying the complexity of the world in an interactive and multidimensional chart, graph or map so that readers can unpack it in their brains, we call it ‘escaping flatland.’ The best examples that achieve this are crafted with code. This course offers a deep dive into technologies and methodologies involved in the production of modern information visualizations. You will work in groups to build a complete information visualization system from data acquisition and processing to visual representation and user interactivity.

Syllabus

Link to Draft Syllabus

Go to syllabus

This is a draft syllabus. The final syllabus will be available here a few days prior to the new course’s first start date.

Pre-requisites

One year of computer science, a course in algorithms and data structures. Knowledge of at least one programming language (e.g. Python/Javascript/Java/C++/Matlab).

Course Note

Students enrolled in this course cannot enroll in the Data Visualization course.

Faculty

Angie Hjort

Faculty

Head of software at Gapminder Foundation. M.Sc. in Human-Computer Interaction with minor in Innovation and Entrepreneurship, KTH Royal Institute of Technology and Aalto University (2014). M.Eng. in Industrial Automation and Control Systems, Ural Federal University (2011). Currently responsible for software efforts of gapminder.org/tools and for developing interactive data pictures. Previous experience building data-intense visualizations for oil platform safety monitoring, user interfaces for an online payment aggregator, and control systems and operator user interfaces for an ore processing factory. With DIS since 2022.

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