The strategy is to create an open professional community to rally innovators to explore the potential of virtual data worlds and thereby advance analytical abilities within corporate and academic sectors. We hope to empower a huge number of curious energetic innovators with a diversity of skills and perspectives to build virtual data worlds. IA Strategy v3The figure illustrates the strategy.

Our Predecessors

The ideas surrounding immersive analytics have been fermenting for decades within several communities. The Science Visualizers have pushed the technology boundaries to generate amazing complex, yet valuable, 3D visualizations. The Data Geeks have extended the scope and power of predictive analytics in countless directions. The Metaverse Pioneers demonstrated compelling examples of large scale virtual simulations shared by dozens. The Data Artisans expanded our awareness of the power of beauty having proper form and function. The CAVE explorers shared virtual mysteries to awe large groups of normal people. Finally, the Video Gamers spawned a huge industry that drove virtual reality to the masses with cheap and reliable technology.

Launch IA Website – Done!

Standing on their shoulders, we launched the ImmersiveAnalytics website to create an open professional community, the goal of which is to define, design, and build virtual data worlds.

But, how will we accomplish this goal? It will take much more than launching a website.

Build and Share Data Worlds

pixabay-tools-864983_640First, the IA community must build and share the first generation of data worlds. This implies the following heads-down hands-on iterative process over the coming year:

  • build, build, build
  • document & share
  • critique & reassess
  • …and then repeat

This website should become a How-To resource that enables you to build useful virtual data objects and data worlds and then apply analytics to understand the behavior of your complex system. We should specify the prerequisite tools and libraries, suggest design steps, and establish evaluation criteria. We should maintain a gallery of examples for downloading and customizing to create your unique data world.

Initially, we need to create just simple data worlds, to illustrate and refine concepts and principles. Later, we need more complex ones, to define interface standards for a modular architecture. Gradually, we need robust platforms that are stable, reliable and secure as a vital component within an enterprise architecture. The goal is to create a Linux-like platform (and ecosystem) for immersive analytics.

Corporate and Academia Partnerships

The IA community should concurrently cultivate and establish close working relationships with both corporations and academia. For corporations, the resulting IA infrastructure must be practical and commercially viable for customers and vendors. For academia, the IA vision should stimulate critical discourse and fresh research investigating new platforms for data discovery and analysis. This fresh look will hopefully suggest new approaches that enable experiments into data comprehension and collaboration.

All Depends on Sharing Ideas

The success of this open community depends entirely on sharing, contributing and synthesizing ideas. As an open community, we have a policy of sharing, with Creative Commons (with Attribution) on discussions and MIT/BSD/Apache license on software. The intent is to stimulate advances in both commercial and academic settings, in both large and small organizations.