  In the process of developing an infrastructure for providing visualization
and visual analytics (VIS) tools to epidemiologists and modeling scientists, we
encountered a technical challenge for applying a number of visual designs to
numerous datasets rapidly and reliably with limited development resources. In
this paper, we present a technical solution to address this challenge.
Operationally, we separate the tasks of data management, visual designs, and
plots and dashboard deployment in order to streamline the development workflow.
Technically, we utilize: an ontology to bring datasets, visual designs, and
deployable plots and dashboards under the same management framework;
multi-criteria search and ranking algorithms for discovering potential datasets
that match a visual design; and a purposely-design user interface for
propagating each visual design to appropriate datasets (often in tens and
hundreds) and quality-assuring the propagation before the deployment. This
technical solution has been used in the development of the RAMPVIS
infrastructure for supporting a consortium of epidemiologists and modeling
scientists through visualization.
