Data visualization in mixed reality with Python

Description

Data visualization is supposed to be our map to information. However, when making charts, we usually just resize lines and circles based on metrics instead of creating data-driven versions of reality. As a result, contemporary charting techniques have a few shortcomings:

• Context reduction: In order to fit a high-dimensional dataset into a chart, you must filter, aggregate, and flatten data, which reduces the full context of information. Without context, most charts show only a part of the story, which can potentially lead to data misinterpretation or misunderstanding.
• Numeric thinking: Humans have a hard time perceiving big numbers. While data visualization is suppose to help us conceptualize large volumes, unless the dataset is carefully prepared, 2D charts rarely give us the intuitive grasp of magnitude.
• Perceptual dehumanization: When examining charts, it’s easy to forget that we are dealing with activity in the real world instead of lines and bars.

Anna Nicanorova explains how augmented, mixed reality (MR) can solve these issues by presenting an intuitive and interactive environment for data exploration. Three-dimensional space provides conditions to create complex data stories with more “realistic" assets, beyond lines and bars. Anna shares the architecture required to create an MR data visualization story with Python, starting with drawing 3D assets in a data-driven way and finishing with deployment on MR devices.