An Environment for Empirical Data Interpretation

While several visualization systems have recently been developed, many application programmers still prefer writing their own code. Why? Because these systems are ill-suited for applications based on empirical data, such as biomedical imaging, robotics, seismic data analysis, and wood classification. Current visualization systems focus on displaying data. But emprical data analysis also needs highly customizable data exploration and interpretation tools which can be adapted to the requirements of different applications. This paper presents EDI, an environment for Empirical Data Interpretation. EDI provides the following capabilities essential to data exploration: (1) Users can probe the data, defining regions of interest with arbitrary shapes. (2) The selected data can be transformed and displayed in many different ways, e.g., several data sets can be displayed together – merged, mixed or overlaid – or they can be shown side-by-side with linked cursors. (3) Linked cursors can be established between several windows showing data sets with arbitrary relationships, e.g., between differently sized images or between images and scatter plots. (4) Data can be displayed on any screen across a computer network, allowing for tele-collaboration arrangements with linked cursors around the world. (5) EDI is user-extensible, allowing programmers to change any component of EDI while keeping the remaining functionality. We demonstrate how EDI can be used in several applications.