Propagating Visual Designs to Numerous Plots and Dashboards

Abstract

Fig. 1. Our novel propagation workflow makes it easy to propagate visual designs to numerous datasets. Reference visualizations are created for data streams, which are associated with several keywords in our ontology. A search and activate process is used to propagate the reference visualisation to other appropriate data streams. (1) Ontology keywords are used to construct a query in our search UI for suitable data stream combinations. (2) Search results consist of ranked data stream combinations that match query parameters, although some results may not be suitable for propagation. (3) A quality assurance step carried out by an expert ensures the visual design is only propagated to suitable data, resulting in new visualizations that are immediately deployed as web pages.

Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations

“…This initial effort has been consolidated by a follow-on project funded by the UKRI/EPSRC through their COVID-19 Rapid Response programme— RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19 . Running until January 2022, this subsequent 12-month project has helped maintain and develop the activity generated through the volunteering, while providing additional resources to enable further capability, research and communication [ 75 , 77 ].…”

Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations

“…This initial effort has been consolidated by a follow-on project funded by the UKRI/EPSRC through their COVID 19 Rapid Response programme -RAMP VIS: Making Visual Analytics an Integral Part of the Technological Infrastructure for Combating COVID-19. Running until January 2022, this subsequent 12-month project has helped maintain and develop the activity generated through the volunteering, while providing additional resources to enable further capability, research and communication [25,56].…”

“…This activity, and our subsequent consolidation through RAMP VIS, has resulted in a central visualization server that offers: hundreds of plots and composite dashboards depicting data on the core pandemic indicators [56] (Fig. 4); analytical agents that automatically transform raw data to be visualized by the central system; a collection of analytical routines and algorithms that offer generic analytical capability for exploring time-series based data; a series of static and interactive visualization prototypes to support the four modelling teams.…”

“…A series of academic articles, both published and in preparation, in the visualization and epidemiological modelling domains, report on specific results that combine technology, design and data successfully in new and revealing ways, e.g. [25,56]. This paper does not focus in detail on the specific developments that took place.…”

Dashboard Design Patterns

“…These decisions include the use of screenspace, dashboard structure, page layout, color schemes, visual representations, etc. In this section, we reflect on our own design process in creating over 7000 dashboards for Covid-19-related data in the UK [31] as well as our discussions from both preparing and running a dashboard design workshop (Sect. 6).…”