Engineering Annotations to Support Analytical Provenance in Visual Exploration Processes

This paper focuses on the fundamental role played by annotations to support provenance analysis in visual exploration processes of large datasets. Particularly, we investigate the use of annotations during the visual exploration of semantic datasets assisted by chained visualization techniques. In this paper, we identify three potential uses of annotations: (i) documenting findings (including errors in the dataset), (ii) supporting collaborative reasoning among teammates, and (iii) analysing provenance during the exploratory process. To demonstrate the feasibility of our approach, we implemented it as a tool support, while illustrating its usage and effectiveness through a series of use case scenarios. We identify the attributes and meta-data that describe the dependencies between annotations and visual representations, and we illustrate these dependencies through a domain-specific model.