Project 5: VisualizationDue Nov. 6
You are to write a GUI Java application that will perform Visualiztion of data with uncertainies. The goal is to presenting data in such a manner that users are made aware of the locations and degree and if possible the meaning of uncertainties that exist. This is a unique project in that there is no right solution to this problem and there is limited prior related work. Part of this work is to review what others have done in this area and to propose something unique in the way that your system works. Here are some techinques/visual queues some of which have been used in previous research in some way to display uncertain information:
Our domain will be for "Disaster Recovery Systems". John Crisotobal will be the specialist in this area and assist/direct the class with this project. Why is there unceratinty and kinds of data: There is all kinds of data that one can imagine you would wish to visualize that would posses uncertainty. Consider environmental/weather/evelation/map data or f intelligence information, etc. Some of this data may be already in a visual form such as the image data whereas others like intelligence reports are not. So, the task of visualizing the data independent of the uncertainty must be accomplished. However, this may not be independent of determining how to display the uncertainties, thier "location", "magnitude", and possibly their "meaning". With each different kind of data, different kinds of uncertainties can exist.
Disaster Recovery: Imagery/Maps with Intelligence Data Now lets consider even a more interesting problem of map building with "intelligence data". In this case, you may have visual data, such as images or maps of the area under consideration but, you can also have additional information potentially from analysis of this data or from other sources. Consider the application of mapping out an area for disaster relief. You could start with a map/image of the area. As human reports come in, you may want to update this map with this information. This information carries with it uncertainties. Displaying the degree of belief/unbelief with each piece of information could be very useful as more than one person reports similar information. With this kind of task, you have the problem of visualizing different kinds of data. Data fusion techniques could be explored.
System Extensibility Consider carefully how you can make this system generic as possible. Consider if you were to have different kinds of uncertain informaiton comming in. Possibly, you can have the user enter the kinds/classes of information that could possibly be presented to the system and have the program automatically choose the visualization technique(s) for displaying each kind of information. This could be done with the definition of a kind of file (and its format) the user would need to create and give to the system along with the data. Another possibility is for the user to interactively enter in this information.
System Interface Functionality Along with simply displaying the information and uncertainties visually to the user, you can offer the user interface tools to alter the display of the data so that they in a sense can analyze the data visually through manipulating it. Some ideas here can include:
Definition of some Terms PseudoColoring involves analysis of the data values
in typically a non-color data/image and the creation of a transformation/mapping
functions that map each possible data value to a color value (not-necessarily
unique).
The Process Click here to see an outline of the stages of this project. You will as a class group on this project. As part of the literature review stage, (see stages) everyone will lead a class discussion on the review of approximately 2 papers on the subject of Uncertainty Visualization. Your other classmates should from this discussion understand how the system generally works. You are to post to blackboard the papers (if they are in electronic form) or their references that you will be reviewing ahead of time. You will be given time in class to work on this project but, it may require time outside of class.
Other Requirements: 1) If images are possible input data, the program must accept either JPEG or GIF images. 2) Program should be a Java GUI applicaiton that you compress into a JAR file for easy use. 3) See other requirements above and below. Some tips:
Sample Data Sets:
Deliverables
Resources I found the following links of the web that may be helpful. Search yourself for previous research in this area. 1) Uncertainty visualiztion: http://www.cse.ucsc.edu/research/slvg/unvis.html [2] Penn State's Uncertainty Vis. center http://www.geovista.psu.edu/research/uncertainty/ [7] International Community for Auditory Display [8] To request Thesis on "Data Uncertainty Sonification and Visualization" [9] van der Wel, Frans J. M. ; van der Gaag, Linda C. ; Gorte, Ben G. H. "Visual exploration of uncertainty in remote-sensing classification." Computers and Geosciences v. 24 no4 (May '98) p. 335-43 [10] Davis, Trevor J. ; Keller, C. Peter. "Modelling and visualizing multiple spatial uncertainties" Computers and Geosciences v. 23 (May '97) p. 397-408 [11] Ehlschlaeger, Charles R. ; Shortridge, Ashton M. ; Goodchild, Michael F. ": Visualizing spatial data uncertainty using animation." Computers and Geosciences v. 23 (May '97) p. 387-95 [12]Mahoney, Diana Phillips. "The picture of uncertainty" Computer Graphics World v. 22 no11 (Nov. 1999) p. 44-6? [13] Suresh K. Lodha, Catherine M. Wilson, Bob Sheehan, "LISTEN: Sounding Uncertainty Visualization", IEEE Visualization '96 , p.??? [14] C. M. Wittenbrink, A. T. Pang and S. K. Lodha, "Glyphs for Visualizing Uncertainty in Environmental Vector Fields", IEEE Transactions on Visualization and Computer Graphics, September 1996, pp. 266-279 [15] A. T. Pang, C. M. Wittenbrink and S. K. Lodha, "Approaches to Uncertainty Visualization", Visual Computer, November 1997, Vol.13, pp. 370-390. [16] Goodchild, M.F., Buttenfield, B.P. and J. Wood. 1995. Introduction to Visualizing Data Validity. In H.M. Hearnshaw and D.J. Unwin (eds) Visualization in GIS. New York: Wiley. |
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© Lynne Grewe |