Setting the Purpose and Identifying Key Factors - Data Visualization: A Successful Design Process - page 29

Note that explanatory visualizations are not limited to just being static in design.
Indeed, some of the most impactive, narrative-driven pieces can be framed within
an interactive or animated construction.
When the function is to explore
Exploratory data visualization design is a slightly different matter compared to
creating an explanatory piece. Here, we are seeking to facilitate the familiarization
and reasoning of data through a range of user-driven experiences. In contrast to
explanatory-based functions, exploratory data visualizations lack a specific, single
narrative. They are more about visual analysis than just the visual presentation of data.
Exploratory solutions aim to create a tool, providing the user with an interface
to visually explore the data. Through this they can seek out personal discoveries,
patterns, and relationships, thereby triggering and iterating curiosities. It also opens
up the possibility for chance or serendipitous findings caused by forming different
combinations of variable displays.
Really, the key feature that differentiates an exploratory piece from an explanatory
piece is the amount of work you have to do as a reader to discover insights. For
explanatory pieces, the designer should do the hard work and create a clear
portrayal of the interesting stories and analysis from a dataset. An exploratory piece
will be more about the readers doing the analysis themselves, putting the effort in to
discover things that strike them as being significant or interesting.