Virtual Reality Technologies (Visual, Haptics, and Audio) in Large Datasets Analysis

Potential Of Vr Technologies For Analysis Of Large Datasets

First, visualization applications range from non-interactive to command-driven systems. In such systems, commands are sent, processed and then comes the result. However, the need to interact with the system has emerged quickly. For example, one would like to zoom, rotate or filter the data. At this point starts the fusion, the interleaving between the query and the result via an iterative process. From there, data analysis is not only guided by the need for effective presentation of data: there are two main components that are the presentation and interaction.

At this point, Shneiderman (1996) identifies four main steps for the implementation of effective interaction process: Overview first, zoom, filter, then details-on-demand. Recently, Yi et al. (2007) have suggested that the interaction process can be supported through seven types of interaction based on users’ intent while interacting with the system. For several researchers of the field, as part of the Human Computer Interaction (HCI) domain, interactive visualization aims at offering a direct and bidirectional communication between people (users) and the visualization system. Bryson (1996) stated that the goal is to create the effect of interacting with things, not with pictures of things. This approach establishes a clear difference between the user and the system: “the user interacts with the system”.