A dynamic graph-based visualization for spreadsheets
Bennett Kankuzi, Yirsaw Ayalew · International Conference on Human-Computer Interaction · 2008
Spreadsheet systems are widely used and highly popular end-user systems. They are used for a variety of important tasks such as mathematical modelling, scientific computation, tabular and graphical data presentation, data analysis and decision making. However, a significant proportion of them have severe quality problems. One of the contributing factors is the invisibility of the data flow structure which is associated with cell formulas. The invisibility of the data flow makes program understanding and debugging very difficult. This paper aims to provide a visualization approach that can simplify understanding and debugging of spreadsheets based on compound fisheye views, the Markov Clustering (MCL) algorithm, and Treemaps. The MCL algorithm helps in visualizing large graphs by generating clusters of cells. Compound fisheye views allows us to view members of a particular cluster while showing their linkages with other clusters. Treemaps help to visualize the depth we are at while navigating a cluster tree. Our initial experiment shows that graph-based visualization using the MCL algorithm generates clusters which match with the corresponding logical areas of a spreadsheet.