The goal of this workshop is to form an IA community and discuss what this community can do to advance discovery science and enable IA-based communication, define the specific research goals, and to discuss metrics to validate IA. We will also explore the ways in which IA differs from and offers benefits well beyond traditional visual analytics and virtual reality. 

Greenville, SC, USA (co-located with IEEE VR conference) Format This half-day workshop will feature a series of invited presentations by leading visualization, virtual reality, and interaction researchers, as well as short paper presentations, panels, and a poster session. Introduction Immersive analytics (IA) investigates how new interaction and display technologies can be used to support analytical reasoning and decision making. IA lies at the intersection of the visualization disciplines in data science, hybrid reality, and 3D interfaces and interaction. The essence of IA consists of deriving insights from data by using powerful display technologies. These technologies augment the human ability to analyze and make sense of the heterogeneous, noisy, often massive and multifaceted datasets common in many scientific disciplines, such as biology, engineering, physics, chemistry, security, health informatics, and brain science. Since “resolution beats memory”, increased screen resolution means that display technologies support the dual modalities of omni-stereo and mono display and can show both structured and unstructured data, breaking the traditional barriers between VR and tiled wall displays from the visualization side and blending augmented reality, virtual reality, and natural user interfaces from the user interface side. Some examples of such hybrid reality environments include

• CAVE2 at UIC,
• YURT at Brown,
• Reality Deck at SUNY,
• Augmentarium at University of Maryland,
• HIVE at Duke, the five-sided La Cueva Grande
• at LANL, and
• AlloSphere at UCSB.