Publications
Despite their ubiquity, authoring dashboards for metrics reporting in modern data analysis tools remains a manual, time-consuming process. Rather than focusing on interesting combinations of their data, users have to spend time creating each chart in a dashboard one by one. This makes dashboard creation slow and tedious. We conducted a review of production metrics dashboards and found that many dashboards contain a common structure: breaking down one or more metrics by different dimensions. In response, we developed a high-level specification for describing dashboards as sections of metrics repeated across the same dimensions and a graphical interface, Quick Dashboard, for authoring dashboards based on this specification. We present several usage examples that demonstrate the flexibility of this specification to create various kinds of dashboards and support a data-first approach to dashboard authoring.
We present Blocks, a formalism that enables the building of visualizations by specifying layout, data relationships, and level of detail (LOD) for specific portions of the visualization. Users can create and manipulate Blocks on a canvas interface through drag-and-drop interaction, controlling the LOD of the data attributes for tabular style visualizations. We conducted a user study to compare how 24 participants employ Blocks and Tableau to complete a target visualization task. Findings from the study suggest that Blocks is a useful mechanism for creating visualizations with embedded microcharts, conditional formatting, and custom layouts. We describe future directions for extending Blocks in visual analysis interfaces.