Three sug­ge­s­ted Pro­jects for a Vi­su­a­li­za­ti­on Cour­se

Project One: Data Sets "IRAS"

With NASA sponsored mission IRAS (Infrared Astronomical Satellite) the entire sky was mapped in 1983 at four far-infrared wavelengths. Following are four data arrays (sky-flux plate 75, HCON 3) representing band 1 (12 micrometers), band 2 (25 micrometers), band 3 (60 micrometers) and band 4 (100 micrometers).  The images show the Milky Way through the center and Lambda Orionis at the lower right. Preprocessing of images is a courtesy of the Infrared Processing and Analysis Center. Destriping and flattening by Gitta Domik..

Each of the four data arrays has the size of 512 * 512 pixels * 1 byte.

p077h3b1.byt (band 1)

 

p077h3b2.byt (band 2)

 

p077h3b3.byt (band 3)

 

p077h3b4.byt (band 4)

 

Download all four data-files in  IRAS.zip:

Assumed task: Astronomers want to find "similar" objects in the images. Can you show "similarity" in measured data?

Possible solution: Merge three images in an RGB or HLS transformation (e.g. map band 4 to red, band 3 to green, band 1 to blue). Similar objects obtain the same color. Examples.

 

Project Two: Data Set "Leaves"

The following table shows (ficticious) measurement results of the growth of leaves from three different types of trees (maple, aspen and pear) at different growing periods:

Type of Tree Age of Leaf Length of Leaf Width of Leaf
Maple 3 weeks 2.2 cm 1.8 cm
Maple 2 months 4.6 cm 5.5 cm
Maple 4 months 8.8 cm 10.0 cm
Aspen 3 weeks 1.2 cm 1.2 cm
Aspen 2 months 3.6 cm 3.6 cm
Aspen 4 months 7.5 cm 7.5 cm
Pear-Tree 3 weeks 3.2 cm 1.2 cm
Pear-Tree 2 months 7.0 cm 2.5 cm
Pear-Tree 4 months 11.0 cm 4.0 cm

Task: Exploration of data - let the students decide on specific tasks.

Hint: A rigorous data model (data characteristics, e.g. what variables are quantitative, ordinal, nominal) helps to avoid errors.

No examples provided.

 

Project Three: Data Set "Flow"

The data set is a snap shot of water flowing through a channel. Winds acting upon the (open) surface of the water create turbulences inside the water. Movements of water particles (caused by the winds) were calculated in a supercomputing class by Lloyd Fosdick, University of Colorado, in 1992. File "field2.irreg" contains data describing the particle movement in a 2d slice perpendicular to the length of the channel. Data is given for a regular 82 x 82 grid in the following format: starting position (x,y,z) and relative movement (u,v,w).

Detailed format of field2.irreg:

Integer value Number of spatial dimensions ("3")
Integer value Number of spatial dimensions ("3")
3 Integer values Integer values describing the extension in each dimension: (Dim_x,Dim_y,Dim_z)=("82, 82, 1")
Integer value Number of spatial dimensions ("3")
Real array of dimension (6,82,82,1) First value "6" describes the number of data entries for each vector, followed by "x,y,z,u,v,w" as described above.


Suggested tasks:

(a) Give a visual overview of the data!
(b) Show Symmetry in the flow!
(c) Where are the quickest / slowest movements (whithout losing sight for the whole flow)?

Discuss advantages/disadvantages/errors of the provided solutions.

Please send back any suggestions and/or complaints to domik[at]uni-paderborn.de