Propagating Visual Designs to Numerous Plots and Dashboards.

Area of Science:

• Epidemiology
• Data Science
• Scientific Visualization

Background:

• Developing visualization and visual analytics (VIS) tools for epidemiologists and modeling scientists presents challenges in applying diverse visual designs to numerous datasets efficiently.
• Limited development resources necessitate streamlined workflows for rapid and reliable deployment of VIS tools.

Purpose of the Study:

• To present a technical solution for the rapid and reliable application of visual designs to numerous datasets within an infrastructure for VIS tools.
• To streamline the development workflow for creating and deploying visualization tools for epidemiological and scientific modeling.

Main Methods:

• Separation of tasks: data management, visual design, and plot/dashboard deployment.
• Utilizing an ontology for a unified management framework of datasets, visual designs, and deployable outputs.
• Implementing multi-criteria search and ranking algorithms for dataset discovery.
• Developing a dedicated user interface for efficient visual design propagation and quality assurance.

Main Results:

• A technical solution has been developed and implemented.
• The solution enables the rapid and reliable application of visual designs to hundreds of datasets.
• The RAMPVIS infrastructure supports a consortium of epidemiologists and modeling scientists through enhanced visualization capabilities.

Conclusions:

• The proposed technical solution effectively addresses the challenge of applying visual designs to numerous datasets.
• The RAMPVIS infrastructure, powered by this solution, enhances support for epidemiologists and modeling scientists.
• Streamlined workflows and efficient resource utilization are key benefits of the developed approach.