Knowledge Visualization aims to facilitate the creation and communication of knowledge through the use of computer and non-computer-based, complementary, graphic representation techniques.....

Scientific- (or data-), and Information visualization are branches of computer graphics and user interface which are concerned with the presentation of interactive or animated digital images to users to understand data. For example, scientists interpret potentially huge quantities of laboratory or simulation data or .... more

Visualization is more than a method of computing! It is a process of transforming information into a visual form enabling the viewer to observe, browse, make sense, and understand the information...more

Information Visualization

Definition: Information Visualisation is a branch of computer graphics concerned with the development of methods of presenting data graphically in an interactive or animated form to enable easier understanding.

While there is some overlap between the related fields of information visualisation and scientific visualisation it is generally understood that information visualisation deals with the representation of abstract non-spatial data taken from such sources as spreadsheets, databases, etc. Scientific visualisation primarily deals with the visual representation of ‘real world’ data, such as climate models and other spatial data.

Development and Use of Information Visualisation

Information visualisationWhile it may seem like an obvious statement, enterprises succeed or fail based on the quality of information they possess. Without adequate knowledge there is little chance for success. However, in addition to this basic truth it is important to understand that there is a difference between possessing knowledge and understanding it in such a way as to allow the enterprise to exploit it successfully.

This is where information visualisation becomes such a powerful tool. Essentially, information visualisation offers a way to transform raw data into a comprehensible graphical format, allowing the user to make decisions based on that data.

Perhaps the best example to describe the way in which visualisations can allow us to better understand data is in Mendeleev’s 1869 Periodic Table of Elements. Mendeleev developed a method by which the known chemical elements could be presented in a grid-like formation, arranged according to their individual attributes. Whether he intended it or not, Mendeleev’s graphical representation of the elements highlighted gaps in our knowledge, allowing scientists to predict where undiscovered elements should fit. By transforming the abstract non-spatial data of chemical elements into a visual representation, Mendeleev created a way for us to better comprehend the data.

This scientific visualisation – graphical visualisation of data from the physical world – eventually led to the field of information visualisation, which deals with the translation of non-spatial data into comprehensible graphical formats.

Business Applications

Information VisualizationAs mentioned above, the ability to understand and communicate abstract data is essential for the success of an enterprise. However, information visualisation is much more than just a method of translating abstract data into a more interesting or visually attractive format.

Instead, a founding tenet of information visualisation – and the measure of the success of any particular visualisation – is that a visualisation should reduce the time required to take in data, make sense of it and draw conclusions from it. One of the most difficult tasks in developing a visualisation is in finding a method of presenting data that can achieve these goals.

Decision-makers require business intelligence to make the right decisions in the shortest possible time. Clearly, then, the ability to communicate dense data in a graphical representation can be of enormous use to decision-makers.

In order to create such representations it is necessary to build a support network charged with the gathering and translation of pertinent data. Data miners can compile data on such things as consumer buying patterns and trends, while the process of translating that data into a graphical format can be entrusted to information visualisation software.

The Future

As computer technology improves – increasing processing power, better graphics applications and analysis software – we can expect to see the field of information visualisation move on in leaps and bounds. New methods of visualising data will eventually push traditional forms of data presentation (such as spreadsheets and basic graphics) into obsolescence.

The first generation of information visualisation has allowed users to become familiar with basic forms of graphical representations of data. In the future we can expect to see even more advanced representations. Today there are many enterprises and academics working to develop new methods of information visualisation, such as AT&T’s IV Research Group, the Pacific Northwest National Laboratory and NIST, as well as a wide range of international conferences focusing on industry-specific applications.

One possibility is the further development of hardware and software related to the field of virtual reality. If it becomes possible to create cost-effective and useful virtual reality devices the future of information visualisation may lie in some sort of ‘full immersion’ technology, in which the user may enter the representation itself to allow them to better understand and manipulate visual data. Whether this type of true 3D representation would actually improve the user’s ability to comprehend the data is as yet unclear, though it does seem likely that in the near future the field of information visualisation will move beyond the constraints of the 2 dimensional computer monitor.