  Data integration is often performed to consolidate information from multiple
disparate data sources during visual data analysis. However, integration
operations are usually separate from visual analytics operations such as encode
and filter in both interface design and empirical research. We conducted a
preliminary user study to investigate whether and how data integration should
be incorporated directly into the visual analytics process. We used two
interface alternatives featuring contrasting approaches to the data preparation
and analysis workflow: manual file-based ex-situ integration as a separate step
from visual analytics operations; and automatic UI-based in-situ integration
merged with visual analytics operations. Participants were asked to complete
specific and free-form tasks with each interface, browsing for patterns,
generating insights, and summarizing relationships between attributes
distributed across multiple files. Analyzing participants' interactions and
feedback, we found both task completion time and total interactions to be
similar across interfaces and tasks, as well as unique integration strategies
between interfaces and emergent behaviors related to satisficing and cognitive
bias. Participants' time spent and interactions revealed that in-situ
integration enabled users to spend more time on analysis tasks compared with
ex-situ integration. Participants' integration strategies and analytical
behaviors revealed differences in interface usage for generating and tracking
hypotheses and insights. With these results, we synthesized preliminary
guidelines for designing future visual analytics interfaces that can support
integrating attributes throughout an active analysis process.
