  Despite the ever-growing popularity of dashboards across a wide range of
domains, their authoring still remains a tedious and complex process. Current
tools offer considerable support for creating individual visualizations but
provide limited support for discovering groups of visualizations that can be
collectively useful for composing analytic dashboards. To address this problem,
we present MEDLEY, a mixed-initiative interface that assists in dashboard
composition by recommending dashboard collections (i.e., a logically grouped
set of views and filtering widgets) that map to specific analytical intents.
Users can specify dashboard intents (namely, measure analysis, change analysis,
category analysis, or distribution analysis) explicitly through an input panel
in the interface or implicitly by selecting data attributes and views of
interest. The system recommends collections based on these analytic intents,
and views and widgets can be selected to compose a variety of dashboards.
MEDLEY also provides a lightweight direct manipulation interface to configure
interactions between views in a dashboard. Based on a study with 13
participants performing both targeted and open-ended tasks, we discuss how
MEDLEY's recommendations guide dashboard composition and facilitate different
user workflows. Observations from the study identify potential directions for
future work, including combining manual view specification with dashboard
recommendations and designing natural language interfaces for dashboard
authoring.
