Annotations in Different Steps of Visual Analytics

Annotations in Visual Analytics (VA) have become a common means to support the analysis by integrating additional information into the VA system. Here, annotations often differ between the individual steps of VA. For example, during data preprocessing it may be necessary to add information on the data, such as redundancy or discrepancy information, while annotations, used during exploration, often refer to the externalization of findings and insights. Describing the particular needs for these step-dependent annotations is challenging. To tackle this issue, we examine the data preprocessing, data cleansing, and data exploration steps for the analysis of heterogeneous and error prone data in respect to the design of specific annotations. By that, we describe their peculiarities for each step in the analysis, and thus aim to improve the visual analytics approach on clinical data. We show the applicability of our annotation concept by integrating it into an existing visual analytics tool to analyze and annotate data from the ophthalmic domain. In interviews and application sessions with experts, we assess the usefulness of our annotation concept for the analysis of the visual acuity development for patients, undergoing a specific therapy.