COMPUTER SCIENCE

Visual Analytics



Visual Analytics

Part 1: Selected Annotated Bibliography

Andrienko, G. Andrienko, N. and Bartling, U. (2008) Visual analytics approach to user-controlled evacuation scheduling. Information Visualization vol. 7 pp. 89-103.

The authors of this research examine the visual analytics in relation to the decision making in the domains of the geographic or spatial and temporal aspects. The research extends the scope of the visual analytics in predicting the natural disasters and natural calamities that occur in the country. They authors suggest that visual analytics is very significant in time-critical applications, which usually pose hard challenges for the humans in the decision making. Thus the model of the research implies that visual analytics is very affective in the decision support. The model is designed on specific tools which aims at supporting the tasks such as emergency events happened in the country and to the people such as the natural disasters like earthquakes, floods and the like. The authors extend that the tools contain the automated scheduling which is based on the genetic algorithm techniques which help evaluating the results and outcomes of the aberrations occur in the country. The authors apply the task-analytical approach for the supporting the planning and analysis of information that is complex and hard to predict.

Cook, K., Earnshaw, R. and Stasko, J. (2007) Guest Editors' Introduction: Discovering the Unexpected. Computer Graphics and Applications vol.27 pp.15-19.

The authors of this research found that visual analytics is combine the human information discourse which includes some form of the interaction with the computer application programs usually the AI programs which enable the program to detect the expected and discovery of the unexpected and large amount of scattered information. The authors also found that visual analytics has several challenges for the growth in the future in the domains of the technologies which include the knowledge management such as libraries and database systems, statistics analysis and tools such as the which predict the large amount of the information more accurately and more precisely for example the systems used in finding the information on the portals of Wikimedia, cognitive science which include the computer systems to understand the various psychological dimensions of the humans and other decision making sciences and arts. The authors rationalize the visual representation model in attaining the intensive analysis as the visual analytics combines the calculated computation of the user needs, visual presentation such as sound and tone of the user and interactive thoughts.

Green, T.M., Ribarsky, W. and Fisher, B. (2009) Building and applying a human cognition model for visual analytics, Information Visualization vol. 8 pp. 1-13.

Green and his co-researchers developed the framework of the visual analytics named enhanced human higher cognition which aims to provide the relevant perceptual models that will increase the flow of human reasoning in the visual analytics. The authors explained the goal of the visual analytics of evaluating and processing large quantities information through the new visualization model that predict the individual needs and demands by providing the computational process of insight and ...