Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY

Data Visualization in Mixed Reality with Python

Anna Nicanorova (Annalect)
3:30pm–4:10pm Thursday, 09/13/2018
Visualization and user experience
Location: 1A 12/14 Level: Beginner

Who is this presentation for?

Data Scientist, Engeneers, Data Viz experts

Prerequisite knowledge

Basic familiarity with Python syntax. The talk is catered towards both novices and advanced users, since the goal is to introduce a new framework that can be executed with Python.

What you'll learn

The talk would be interesting to anyone who : * wants to create for AR/MR experiences but doesn’t know where to start * is interested in practical use of AR/MR (beyond entertainment) * believes there is a better way to visualize data The audience will get an * a live demo and hopefully inspiration on alternatives to current charts and graphs in data visualization * the code stack required to create a MR project * knowledge on how to deal with data-driven visualization in 3 dimensions

Description

Data Visualization charts are supposed to be our map to information. However, when making charts, customarily we are just re-sizing lines and circles based on metrics instead of creating data-driven version of reality. The contemporary charting techniques have a few shortcomings (especially when dealing with high-dimensional dataset):

- Context Reduction: in order to fit a high-dimensional dataset into a chart one needs to filter/ aggregate/ flatten data which results in reduction of full context of information. Without context most of the charts show only a part of the story, that can potentially lead to data misinterpretation/misunderstanding.
- Numeric Thinking: naturally humans have hard time perceiving big numbers. While data visualization is suppose to help us to conceptualize large volumes, unless the dataset is carefully prepared, 2D charts rarely give us the intuitive grasp of magnitude.
- Perceptual de-humanization: when examining charts it is easy to forget that we are dealing with activity in real world instead of lines/bars.
Augmented/Mixed Reality can potentially solve all of the issues listed above 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). The talk would present the architecture required to create MR data visualization story with Python (70% of architecture), starting with drawing 3D assets in a data-driven way and finishing with deployment on MR devices.

Photo of Anna Nicanorova

Anna Nicanorova

Annalect

Anna Nicanorova is Director of Annalect Labs – space for experimentation and rapid prototyping within Annalect. During her time at Annalect she has worked on numerous data-marketing solutions: attribution, optimizers, quantification of content and image recognition technology. In 2015 Anna was part of Annalect team, that won I-Com Data Science Hackathon 2015.

Anna is Co–Founder of Books+Whiskey meetup and coding volunteer teacher with ScriptEd. She holds an MBA from University of Pennsylvania – The Wharton School and BA from Hogeschool van Utrecht.

Leave a Comment or Question

Help us make this conference the best it can be for you. Have questions you'd like this speaker to address? Suggestions for issues that deserve extra attention? Feedback that you'd like to share with the speaker and other attendees?

Join the conversation here (requires login)