Sonification of Complex Data Sets: An Example from Basketball

Frances L. Van Scoy

Status and Goal

We have now written a C++ application which takes as input our rules for generating music and the data for a particular basketball game and generates a MIDI file for the resulting music which is then played on a Macintosh G3 computer using the Finale Allegro 98 package. We are now constructing by hand data files from hand written notes taken at WVU basketball games during the 1997-8 and 1998-9 seasons. We anticipate that the music generated from these two seasons will be noticably different. During 1997-8 the team had five strong seniors who played almost the entire game, with rest breaks provided by two other seniors, and the team was quite successful, going to the Sweet Sixteen. In 1998-9 the team had few experienced players, and a core of five to seven strong players never emerged. This team lost more games than it won. We anticipate that more frequent substitutions and playing time by more different players during the 1998-9 season will lead to obviously different sounding music than that generated from games of the 1997-8 season. (To test this, we will have to disable indicating relative score and which team is leading, or compare only games in which WVU won.)

So far our evaluation of different schemes for generating music has been quite informal, testing melodies on each other, on others who work in our lab, and on visitors to the lab. One team member has an undergraduate degree in psychology, and during summer 1999 he will develop and perform more formal experiments with naive users.

More importantly than improving our method of representing basketball games, we intend to apply the lessons learned from working with basketball to analysis of three-dimensional data sets. In particular we want to provide a viewer of a 2-d projection of 3-d data with clues about how to change viewing perspective to see interesting properties of the data. Figure 7 shows a simple example in which we project into the x-y plane two "clouds" of points, each cloud parallel to the x-y plane.

Figure 7 Projection of 3-Data into the x-y Plane

This projection could represent data arranged in many ways in Cartesian space, including those shown in Figure 8, in which the two data clouds are either disjoint or intersecting.

Figure 8 3-D Views of Data, Showing Disjoint and Intersecting Red and Green Clouds

We plan to generate music that will give auditory clues about how far apart these clouds are along the z axis by generating music in which the relative distance of a point in a particular cloud from the x-y plane is mapped to pitch. This will require a more sophisticated scheme for generating music than is currently being used with the basketball data

As in Meijer's The vOICe, we will scan the 2-d projection from left to right, generating music (as distinguished from sound) for each column. We will provide a bar which shows which column in the image is producing the current music. The user may click on the mouse button to mark that particular column and may later zoom in to the data using two of these bars to bracket the region of interest. The user may also choose to scan the projection from top to bottom. We hope to generate music that will guide the user in choosing viewing perspectives of the data.