In this track, we look at everything from collection to display, and the engineering of interfaces that turn raw information into useful knowledge and changed behaviors.
Who should attend: Developers, designers, information architects; UX professionals; journalists and marketers
Noah Iliinsky strongly believes in the power of intentionally crafted communication. He has spent the last several years researching, writing, and speaking about best practices for designing visualizations, informed by his graduate work in user experience and interaction design. He is a frequent speaker in both industry and academic contexts. He has a master’s in Technical Communication from the University of Washington, and a bachelor's in Physics from Reed College. Noah works as a Visualization Expert at IBM's Center for Advanced Visualization.
Julie Steele is the Content Editor for Strata at O'Reilly Media. She is co-author of Beautiful Visualization and Designing Data Visualizations. She finds beauty in exploring complex systems, and thinks in metaphors. She is particularly drawn to the visual medium as a way to understand and transmit information.
Murray Hill Suite
Tutorial Please note:
to attend, your registration must include Tutorials
Learn how to find beauty in data. The beauty of a visual is that it can communicate so much. As we become more sophisticated with the amount of data we can harness, it will become more important for us to be equally good at visually communicating that data. This workshop will guide attendees through the process of learning a method that will aide in selecting the right visualization.
Using a one of a kind dataset of gas and electric energy usage throughout the Chicago area, we built a tool that encourages Chicago citizens to be more energy efficient. The visual tool aligns with the goals of the City of Chicago while also being informative, educational, and encouraging action.
Effective visualization techniques and interaction methods for large data sets.
How can a data-driven visualization tell multiple interplaying stories, and achieve a viable result in an abstract visual composition?
Readers and preparers of graphs: Learn to recognize and avoid some common graphical mistakes to understand your data better and make better decisions from data. Examples and mistakes will be different from those used in a similar presentation at the 2011 conference.
This talk discusses the broad design considerations necessary for effective visualizations. Attendees will learn about purpose, content, structure, and formatting. We will also discuss why they must be selected in this order, and discuss the importance and impact each has on your visualization.
Visualizations of big graphs often look like spaghetti and can be difficult to use. Working backwards from the analytic questions, we will show some very different 2D and 3D visualizations for social networks. We'll also cover some of the challenges and discuss some open source tools.