David McColgin, Paul Hoover, and Mark Igra
Abstract —The DataSpace for HIV vaccine studies is a discovery
tool available on the Web to hundreds of investigators. We designed it
to help them better understand activity in the field and explore new
ideas latent in completed research. In the past, only small central
groups with specific goals have integrated the data from these studies.
Further data integration and broader access were hindered by both
experimental complexity and a research culture that treats data as
proprietary. Responding to a call for change by leading vaccine
organizations, the DataSpace harmonizes immunoassay results and study
metadata so that a broader research community can pursue more flexible
discovery than centrally planned analyses. Insights from human-centered
design and beta evaluation suggest important differences from typical
visual analytics needs that may inform similar efforts in open
scholarship. The contribution of this paper is to elucidate some of
these differences and demonstrate an application that addresses them. We
made several changes to familiar visualizations to support key tasks
such as identifying and filtering to a cohort of interest, making
meaningful comparisons of time series data from multiple studies that
have different plans, and preserving analytic context when making data
transformations and comparisons that would normally exclude some data.
Additional features provide the detailed metadata needed to plot and
interpret others’ work. We also discuss beta evaluation and the path to
achieving domain impact.
Index Terms —Hypothesis forming, Time series visualization,
Visual knowledge discovery, Vaccines, Public health