Details-First, Show Context, Overview Last: Supporting Exploration of Viscous Fingers in Large-Scale Ensemble Simulations

Abstract

Visualization research often seeks designs that first establish an overview of the data, in accordance to the information seeking mantra: "Overview first, zoom and filter, then details on demand". However, in computational fluid dynamics (CFD), as well as in other domains, there are many situations where such a spatial overview is not relevant or practical for users, for example when the experts already have a good mental overview of the data, or when an analysis of a large overall structure may not be related to the specific, information-driven tasks of users. Using scientific workflow theory and, as a vehicle, the problem of viscous finger evolution, we advocate an alternative model that allows domain experts to explore features of interest first, then explore the context around those features, and finally move to a potentially unfamiliar summarization overview. In a model instantiation, we show how a computational back-end can identify and track over time low-level, small features, then be used to filter the context of those features while controlling the complexity of the visualization, and finally to summarize and compare simulations. We demonstrate the effectiveness of this approach with an online web-based exploration of a total volume of data approaching half a billion seven-dimensional data points, and report supportive feedback provided by domain experts with respect to both the instantiation and the theoretical model.

DarkSky Halos: Use-Based Exploration of Dark Matter Formation Data in a Hybrid Immersive Virtual Environment

“…Two of the most novel aspects of this immersive analytics application are its activity-focus and its details-first design. As also noted by Chen et al (2016) and Luciani et al (2019) were the first to remark, in 2016, that in "many scenarios, we often observe that an experienced viewer may find (overview first and details on demand) frustrating, as the viewer knows exactly where the interesting part of a detailed representation is." Chen's observation is reflected in a vast number of works in scientific visualization that support explicitly spatial feature exploration first, and display the rest of the information primarily for context (e.g., Doleisch et al, 2003;Zhang et al, 2003;Hauser, 2005;Sherbondy et al, 2005;Caban et al, 2007;Jianu et al, 2009;Potter et al, 2009;Kehrer and Hauser, 2013).…”

“…Chen's observation is reflected in a vast number of works in scientific visualization that support explicitly spatial feature exploration first, and display the rest of the information primarily for context (e.g., Doleisch et al, 2003;Zhang et al, 2003;Hauser, 2005;Sherbondy et al, 2005;Caban et al, 2007;Jianu et al, 2009;Potter et al, 2009;Kehrer and Hauser, 2013). The "Details-first, show context, overview last" model (Luciani et al, 2019) we adopted in this work specifically applies to visual analytics processes where the features drive both the relevant context for the exploration process and the calculation of summarization overviews.…”

“…For example, in flow simulation, scientists work on the same problem for months." While the theoretical work of Luciani et al (2019) provides a scientific workflow framework for this paradigm, no immersive applications document its application in practice.…”

“…We further noted the lack of a precise mathematical formula for identifying the halo features: the catalogs are derived on the basis of expert-tweaked thresholds. Given these observations, we considered the design problem from the perspective of scientific workflow theory and of the three known top-design visualization paradigms: "overview-first" (Shneiderman, 1996), "search-first" (van Ham and Perer, 2009), and "details-first, " later formally documented in the visualization literature as a theoretical model (Luciani et al, 2019). Following the workflow activities, together with the domain expert we agreed on an overall design that emphasized the features of interest first, then provided spatial and temporal context information, and finally provided a summarization overview of the data (Luciani et al, 2019).…”

Ten simple rules to create biological network figures for communication

“…However, an extremely dense network with many overlapping nodes will not provide effective overview or context. Alternative models to the "overview-first" paradigm [30] include a "search-first" paradigm [31] and a "details-first" paradigm [32], depending on the interests and background of the target audience.…”