Data Visualization

1.Global description of the technological area

Visualization is a tool used to explore complex (or even simple) data across a large number of domains. Immersive visualization is characterized by the use of virtual reality and its interaction with data, relevant aspects for scientific evaluation and also in fields such as training and education. This visualization allows active interaction with possible representations, for example, in drug design “you can walk through brains or molecules, and you can fly trough galaxies”.

The requirements and level of interaction vary depending on whether this “walk” is for professional use, for students or for the general public. Data immersion could take place by the user or in a shared environment, where it is explored and evaluated with others.

The data can be static, or it could be immersed in dynamic processes, in addition the data must be visible in multiscale form. Three-dimensional representation of real or modelled data is important for understanding the data and for decision making after this understanding, a relevant topic to several fields, especially in those datasets that are growing exponentially.

Even when most analysis tools are computer-generated algorithms, human vision highly sensitive to patterns, trends and anomalies.

One can think of virtual reality as a specific means to achieve effective visualizations. Virtual reality has a number of features that can contribute to the success of a visualization application, especially when that application must address with high-dimensional data, large volumes of data and/or highly complex data.

One of the great strengths of virtual reality is its stated goal of offering users more accessible, more intuitive and more powerful interaction capabilities. One way to understand this concept is to imagine that a user receives a foreign object that can be held in one hand.

What is the natural thing for the user to do? First, the user will rotate the object to examine it, just as virtual reality can be used to provide users with different views of an object or scene. Then, the user can the click on the object to determine some of its properties or to trigger a behavior, just as one can use virtual reality to provide users with gestural interfaces for direct interaction with virtual objects.

2. EVOLUTION

Although there is strong evidence that virtual reality systems can offer significant advantages over conventional display systems for visualization applications, many challenges remain. Below are some of the greatest barriers to the use of virtual reality as the main platform for visualization in many fields.

• Fidelity. Fidelity has two “sides”, in a sense, fidelity can refer to the resolution of data and/or displays of the data. One can think in terms of the resolution of a dataset or a display. Another aspect of fidelity is in the representation of the data itself. A primary unanswered question is: “How much fidelity is enough”, i.e. how much fidelity must an application and/or its display system have in order to achieve a specific result?
• Multimodal displays. While display technology is relatively mature and 3D audio displays are of very high quality, much work needs to be done to advance the state of the art in displays for others senses (haptic, olfactory, vestibular and gustatory) and in the integration of multimodal displays to provide a perfect sensory environment for the user. Perhaps the greatest challenge of all is the need for a solid theory of multisensory perception to guide the developer in mapping different types of data to different sensory modalities.
• Technical fragility. The hardware and software used in virtual reality is still fragile. The lack of a mass market has hampered manufacturers’ desire to build more robust systems and invest in the needed research to solve fundamental engineering problems (such as latency).
• Software inaccessibility. Available software system, even those that are commercially available, are notoriously difficult to use. It takes a lot of patience and experience to become a competent developer of virtual reality applications of any real complexity.

USE CASES AND APPLICATIONS

Below are several cases of using Virtual Reality for data visualization.

ARCHITECTURAL DESIGN

Several projects have used virtual reality in architectural design and collaborative visualization to exploit the capacity of virtual reality for multiple perspectives by users. These perspectives, which include multiple mental models and multiple visual points of view, allow virtual reality to be applied in the early stages of the design process.

DEFENCE

In this field, several projects have developed Battlespace visualization applications based on virtual reality. Modern battlespace extends from the ocean floor to low earth orbit. Therefore, 3D visualizations that support powerful direct interaction techniques offer significant value to military planners, trainers and operators.

COSMOLOGY

Virtual reality is a useful tool for visualizing numerical and observational cosmology data. These applications support multiscale visualization of large, multi-level, time-dependent datasets using an immersive display and a gesture interface that facilitates direct interaction with the data

GENOME VISUALIZATION

Virtual reality has been used to develop applications for peer-to-peer comparison between sets of groups generated form different gene expression datasets. They show the distribution of overlaps between two sets of hierarchical groups, based on hepatocellular carcinomas and hepatoblastomas.

METEOROLOGY

Meteorologists often use 2D graphics or text to display their data. Such an approach makes it difficult to visualize the 3D atmosphere. Several projects have addressed the problem of comparing and correlating multiple layers by using an immersive virtual environment for true 3D visualization of data.

OCEANOGRAPHY

These applications provide researchers with the ability to interactively alter ocean parameters and communicate those changes to an ocean model that calculates the solution.

PROTEIN STRUCTURES

The protein structures are large and complex. Large format virtual reality systems support the visualization of such data and also the collaboration of small teams that analyse the data.

SOFTWARE SYSTEMS

Many computer programs exceed a million lines of code. The ability to really understand programs of such magnitude is rare. Visualization of such systems provide a means of understanding the system and extending or modifying it collaboratively.

STATISTICAL DATA AND BIG DATA

Several projects have developed virtual reality-based applications for the analysis of high dimensional statistical data. In addition, the virtual reality approach is proving to be superior than the desktop approach in terms of structural detection tasks.

VECTOR FIELDS

Real-time visualization of particle traces using virtual environments can assist in the exploration and analysis of complex 3D vector fields.

VEHICLE DESIGN

The use of increasingly complex simulations of finite element (FE) vehicles during crashes has led to the use of virtual reality techniques to visualize calculation results. These applications receive geometry and physical property data as input and provide the means for the user to enter a virtual crash and interact with any part of the vehicle to better understand the implications of the simulation.

VIRTUAL WIND TUNNEL

One of the first successful demonstrations of virtual reality as a visualization tool was the development of the virtual wind tunnel at the NASA/ Ames Research Center. Given the high cost of maintaining and operating wind tunnels and the limited regimes (both wind speed and size of the wind surface), the virtual wind tunnel offers significant potential to reduce the cost and expand the availability of wind tunnel experiments.

HYDROCARBON EXPLORATION AND PRODUCTION

In recent years, virtual reality has had a growing impact on the exploration and production of hydrocarbons, specifically oil and gas. In 1997, there were only two large-scale visualization centres in the oil and gas industry. In 2000, the number had increased to over 20. More importantly, these systems have had a demonstrable return on investment in terms of improved speed and successful decision making for exploration and production activities.