INFORMATION VISUALIZATION

Introduction:

The primary focus on Information Retrieval Systems has been in the areas of indexing, searching and clustering versus information display. This has been due to the inability of technology to provide the technical platforms needed for sophisticated display, academic's focusing on tile more interesting algorithmic based search aspects of information retrieval, and the multi-disciplinary nature of the human-computer interface (HCI).

The beginnings of the theory of visualization began over 2400 years ago. The philosopher Plato discerned that we perceive objects through the senses, using the mind. Our perception of the real world is a translation from physical energy from our environment into encoded neural signals. The mind is continually interpreting and categorizing our perception of our surroundings. Use of a computer is another source of input to the mind's processing functions. Information visualization is a relatively new discipline growing out of the debates in the 1970s on the way the brain processes and uses mental images. It required significant advancements in technology and information retrieval techniques to become a possibility.

Information visualization techniques have the potential to significantly enhance the user's ability to minimize resources expended to locate needed information. The way users interact with computers changed with the introduction of user interfaces based upon Windows, Icons, Menus, and Pointing devices (WIMPs). In information retrieval, the process of getting to the relevant details starts with filtering many items via a search process. The result of this process is still a large number of potentially relevant items. There are many areas that information visualization and presentation can help the user:

a. reduce the amount of time to understand the results of a search

b. yield information that comes from the relationships between items

c. perform simple actions that produce sophisticated information search

Cognition and Perception

As computers displays became ubiquitous, man-machine interfaces focused on treating the display as an extension of paper with the focus on consistency of operations. The advent of WIMP interfaces and simultaneous parallel tasks in the user work environment expanded the complexity of the interface to manipulate the multiple tasks. The advancements in computer technology, information sciences and understanding human information processing are providing the basis for extending the human computer interface to improve the information flow, thus reducing wasted user overhead in locating needed information. Although the major focus is on enhanced visualization of information, other senses are also being looked at for future interfaces. The audio sense has always been part of simple alerts in computers.

Background:

A significant portion of the brain is devoted to vision and supports the maximum information transfer function from the environment to a human being. Until then perception was considered a data collection task and thinking as a higher level function using die data. He contended that visual perception includes the process of understanding the information, providing an ongoing feedback mechanism between the perception and thinking. He further expanded his views arguing that treating perception and thinking as separate functions trots the mind as a serial automata.

Visualization is the transformation of information into a visual form which enables the user to observe and understand the information. This concept can be extended where the visual images provide a fundamentally different way to understand information that treats the visual input not as discrete facts but as an understanding process.

Shifting the information processing load from slower cognitive processes to faster perceptual systems significantly improves the information-carrying interfaces between humans and computers. An understanding of the way the cognitive processes work provides insights for the decisions on which of the presentations will maximize the information passing and understanding.

Aspects of the Visualization Process:

One of the first-level cognitive processes is preattention, that is, taking the significant visual information from the photoreceptors and forming primitives. In Figure 8.1 the visual system detects the difference in orientations between the left and middle portion of the figure and determines the logical border between them.

The preattentive process can detect the boundaries between orientation groups of the same object. For example, a rotated square requires more effort to recognize it as a square. As we migrate into characters, the problem of identification of the character is affected by rotating the character in a direction not normally encountered. It is easier to detect the symmetry when the axis is vertical. Figure 8.2 demonstrates these effects.

Another visual factor is the optical illusion that makes a light object on a dark background to appear larger than if the item is dark and the background is light. Making use of this factor suggests that a visual display of small objects should use bright colors. An even more complex area is the use of colors. Colors have many attributes that can be modified such as hue, saturation and lightness. Hue is the physiological attribute of color sensation. Saturation is the degree to which a hue is different from a gray line with the same lightness, while lightness is the sensation of the amount of white or black.

Another visual cue that can be used is spatial frequency. The human visual and cognitive system tends towards order and builds an coherent visual image whenever possible. The multiple spatial channel theory proposes that a complex image is constructed from the external inputs, not received as a single image. The final image is constructed from multiple receptors that detect changes in spatial frequency, orientation, contrast, and spatial phase. Spatial frequency is an acuity measure relative to regular light-dark changes that are in the visual field or similar channels. A cycle is one complete light-dark change.

Information Visualization Technologies

The theories associated with information visualization are being applied in commercial and experimental systems to determine the best way to improve the user interface, facilitating the localization of information. They have been applied to many different situations and environments (e.g., weather forecasting to architectural design). The ones focused on Information Retrieval Systems are investigating how best to display the results of searches, structured data from DBMSs and the results of link analysis correlating data.

Structured databases are important to information retrieval because structured files are the best implementation to hold certain citation and semantic data that describe documents. Link analysis is also important because it provides aggregate-level information within an information system. Rather than treating each item as independent, link analysis considers information flowing between documents with value in the correlation between multiple documents.

One way of organizing information is hierarchical. A tree structure is useful in representing information that ranges over time (e.g., genealogical lineage), constituents of a larger unit (e.g., organization structures, mechanical device definitions) and aggregates from the higher to lower level (e.g., hierarchical clustering of documents). A two-dimensional representation becomes difficult for a user to understand as the hierarchy becomes large. The Cone-Tree is a 3-Dimensional representation of data. Compared to other hierarchical representations (e.g., node and link trees) the cone makes the maximum information available to the user providing a perspective on size of each of the subtrees (Gershon-95a, Robertson-93).

An example of a Cone-Tree is shown in Figure 8.4. The squares at the leaf nodes in tree are the actual documents. Higher level nodes can be considered centroids representing the semantic of the child nodes. Where the database is large, the boxes may represent a cluster of related items versus a single item. These clusters could be expanded to lower levels of the tree. The perspective wall divides the information into three visual areas with the area being focused on in the front and other areas out of focus to each side (see Figure 8.5). This allows the user to keep all of the information in perspective while focusing on a perticular area.

Another technique used in display of hierarchical information is tree maps. This technique makes maximum use of the display screen space by using rectangular boxes that are recursively subdivided based upon parent-child relationships between the data. A particular information work space focused on articles on computers may appear as shown in Figure 8.6.

The size of the boxes can represent the number of items on a particular topic. The location of the boxes can indicate a relationship between the topics. In Figure 8.6, the CPU, OS, Memory, and Network management articles are all related to a general category of computer operating systems versus computer applications which are shown in the rest of the figure.