Authors:
Neven ElSayed, Kim Marriott, Ross T. Smith, Bruce H. Thomas
Augmented reality (AR) is the technology of enriching the physical world with additional information [1], converting users' physical environments into their user interfaces. This goal is becoming more attainable with the growth of data production and streaming technology, especially with the rapid improvement of AR displays.
Insights
→ Situated analytics (SA) aims to enhance information understanding with an in situ, analytical, interactive user interface.
→ The presented illustration shows the potential use and benefits of SA, highlighting the strength of using data storage, processing, and analysis for making decisions.
→ The contextual and situational awareness of SA interaction can help align and explore big and multidimensional data.
Every day, we interact with and stream large amounts of data. Among these data items, some have explicit relationships, such as that between groceries and their ingredients. Others have implicit relationships, such as the effect a supermarket product may have on a shopper's goals, such as those involving fitness and budgets. The decisions we make in our daily lives are based on our available information, time, budgets, preferences, and constraints. As such, enhancing ways of interacting and visualizing with data will allow us to make better and more-informed decisions. Stating that "existing interaction systems are blind," James Thomas [2] identified a gap in existing visualization interactions for investigation and decision making. The decision-making algorithm's main challenge is the need for high-level understanding of the data with no predefined hypothesis, also known as sensemaking [3]. Sensemaking is an investigative process through which humans can enhance their understanding of their experiences. Recently, visual analytics (VA) was introduced as the science of visual investigation. Driven by human observation, VA allows users to investigate multidimensional data in order to discern relationship patterns.
This article presents situated analytics (SA) [4,5,6], a novel merging of AR and VA that combines an immersive information-presentation element from AR with the analytical reasoning concepts and tools from VA. SA allows users to explore and analyze information about objects in their physical environment. Users receive situated and abstract information for their overall user interface, interacting with physical and virtual content in large spaces—the physical scene.
The following illustration depicts the concept of situated analytics as a day-in-the-life comic strip. It provides an example of everyday situated information visualization based on different parameters and resources. The strip demonstrates the use of SA throughout the day, helping a user make informed decisions based on the rich amount of data now available to them.
Sidebar: SA Challenges
This comic strip includes a large and varied array of SA techniques to show the possibilities and is not intended to convey an actual use case. It does, however, introduce new visualization and interaction challenges for SA due to the dynamic nature of displaying virtual information on the real scene, such as:
- Cluttered display
- Dynamic representation surfaces; the physical objects
- Dynamic display background; the real scene
- Immovable physical objects
- Off-screen objects
- Large interaction space; the real environment
- Device-dependent input controls
- Enabling interaction with the physical objects and their associated information
- Enabling a smooth transition between interacting with the physical object and the virtual information.
References
1. Azuma, R.T. A survey of augmented reality. Presence: Teleoperators and Virtual Environments 6, 4 (1997), 355–385.
2. Thomas, J.J. Illuminating the Path: The Research and Development Agenda for Visual Analytics. IEEE, 2005.
3. Pirolli, P. and Card, S. The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. Proc. of the International Conference on Intelligence Analysis. 2005, 2– 4.
4. ElSayed, N.A.M., Thomas, B.T., Smith, R.T., Marriott, K., and Piantadosi, J. Using augmented reality to support situated analytics. Proc. of Virtual Reality 2015. IEEE, 2015.
5. ElSayed, N.A.M., Thomas, B.T., Marriott, K., Piantadosi, J, and Smith, R.T. Situated analytics: Demonstrating immersive analytical tools with augmented reality. Journal of Visual Languages & Computing 36 (2016), 13–23.
6. Thomas, B.H. et al. Situated analytics. In Immersive Analytics. Lecture Notes in Computer Science vol. 11190. Springer, Cham, 2018, 185–220.
Authors
Neven ElSayed is a senior researcher at Know Center. ElSayed earned a Ph.D. in computer science at the University of South Australia and was awarded the Michael Miller Medal for outstanding thesis in 2017. ElSayed research includes situated analytics, immersive analytics, augmented reality, and human computer interaction. [email protected]
Kim Marriott leads the Department of Human-Centred Computing at Monash University in Australia. His research includes data visualization and assistive technology, with a focus on improving access for people who are blind or have low vision to graphical information. [email protected]
Ross T. Smith is an associate professor at the University of South Australia. He leads the Wearable Computer Laboratory and is a member of the Australian Research Centre for Interactive and Virtual Environments (IVE). His research includes virtual/augmented/mixed reality, novel interaction devices, deformable surfaces, input device hardware development, and user interface design. [email protected]
Bruce H. Thomas is an emeritus professor at the University of South Australia. His current research interests include user interfaces, augmented reality, virtual reality, visualization, wearable computers, and the use of cognitive psychology in virtual environments research. [email protected]
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