Large-Scale Overlays and Trends: Visually Mining, Panning and Zoomingthe Observable Universe

Luciani, Timothy; Cherinka, Brian; Oliphant, Daniel Q.; Myers, Sean; Wood‐Vasey, W. M.; Labrinidis, Alexandros; Marai, G. Elisabeta

doi:10.1109/tvcg.2014.2312008

Cited by 17 publications

(11 citation statements)

References 25 publications

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“…Such requirements go beyond usability and user experience goals: 1) Scalability influences more than just visual scalability (would we be able to store and process on the fly a petascale dataset? [28, 33]); 2) Privacy can affect the publication of a project—several interdisciplinary projects nearly-failed publication because data was revealed to be private, sensitive, or proprietary [23, 51]; 3) Certain scientific user groups have a strong preference for desktop applications (as opposed to web-based) [58], and other groups expect cross-platform compatibility [46]. All the factors above influence the design and outcome of a project.…”

Section: Network Modelmentioning

confidence: 99%

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

Marai

2018

IEEE Trans. Visual. Comput. Graphics

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Although visualization design models exist in the literature in the form of higher-level methodological frameworks, these models do not present a clear methodological prescription for the domain characterization step. This work presents a framework and end-to-end model for requirements engineering in problem-driven visualization application design. The framework and model are based on the activity-centered design paradigm, which is an enhancement of human-centered design. The proposed activity-centered approach focuses on user tasks and activities, and allows an explicit link between the requirements engineering process with the abstraction stage—and its evaluation—of existing, higher-level visualization design models. In a departure from existing visualization design models, the resulting model: assigns value to a visualization based on user activities; ranks user tasks before the user data; partitions requirements in activity-related capabilities and nonfunctional characteristics and constraints; and explicitly incorporates the user workflows into the requirements process. A further merit of this model is its explicit integration of functional specifications, a concept this work adapts from the software engineering literature, into the visualization design nested model. A quantitative evaluation using two sets of interdisciplinary projects supports the merits of the activity-centered model. The result is a practical roadmap to the domain characterization step of visualization design for problem-driven data visualization. Following this domain characterization model can help remove a number of pitfalls that have been identified multiple times in the visualization design literature.

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Section: Network Modelmentioning

confidence: 99%

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

Marai

2018

IEEE Trans. Visual. Comput. Graphics

Self Cite

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“…These glyphs can also be applied to general temporal data with multiple variables that include both numerical (height) and categorical data (color). Such datasets exist in other domains where symmetric/asymmetric time-dependent behavior is of interest, for instance in the analysis of spectrograph data in astronomy, 50 in the analysis of financial data, or in the analysis of Electronic Health Records. The mosaic-matrix nesting approach may find application in other spatially dense temporal datasets.…”

Section: Discussionmentioning

confidence: 99%

RemBrain: Exploring Dynamic Biospatial Networks with Mosaic Matrices and Mirror Glyphs

Ma¹,

Pellolio²,

Llano³

et al. 2017

jist

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We introduce a web-based visual comparison approach for the systematic exploration of dynamic activation networks across biological datasets. Understanding the dynamics of such networks in the context of demographic factors like age is a fundamental problem in computational systems biology and neuroscience. We design visual encodings for the dynamic and community characteristics of these temporal networks. Our multi-scale approach blends nested mosaic matrices that capture temporal characteristics of the data, spatial views of the network data, Kiviat diagrams and mirror glyphs that detail the temporal behavior and community assignment of specific nodes. A top design specifically targeted at pairwise visual comparison further supports the comparative analysis of multiple dataset activations. We demonstrate the effectiveness of this approach through a case study on mouse brain network data. Domain expert feedback indicates this approach can help identify trends and anomalies in the data.

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“…Continuous level of detail of point clouds have also been used to interactively explore billions of particles (Fraedrich et al, 2009). Luciani et al (2014) have tackled the visual analysis of astronomy images. Last but not least, a few works have attempted to visualize dark matter data, as we do (Almryde and Forbes, 2015;Christoudias et al, 2015;Hazarika et al, 2015).…”

Section: Related Workmentioning

confidence: 99%

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

et al. 2019

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Hybrid virtual reality environments allow analysts to choose how much of the screen real estate they want to use for Virtual Reality (VR) immersion, and how much they want to use for displaying different types of 2D data. We present the use-based design and evaluation of an immersive visual analytics application for cosmological data that uses such a 2D/3D hybrid environment. The applications is a first-in-kind immersive instantiation of the Activity-Centered-Design theoretical paradigm, as well as a first documented immersive instantiation of a details-first paradigm based on scientific workflow theory. Based on a rigorous analysis of the user activities and on a details-first paradigm, the application was designed to allow multiple domain experts to interactively analyze visual representations of spatial (3D) and nonspatial (2D) cosmology data pertaining to dark matter formation. These hybrid data are represented at multiple spatiotemporal scales as time-aligned merger trees, pixel-based heatmaps, GPU-accelerated point clouds and geometric primitives, which can further be animated according to simulation data and played back for analysis. We have demonstrated this multi-scale application to several groups of lay users and domain experts, as well as to two senior domain experts from the Adler Planetarium, who have significant experience in immersive environments. Their collective feedback shows that this hybrid, immersive application can assist researchers in the interactive visual analysis of large-scale cosmological simulation data while overcoming navigation limitations of desktop visualizations.

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Large-Scale Overlays and Trends: Visually Mining, Panning and Zoomingthe Observable Universe

Cited by 17 publications

References 25 publications

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

RemBrain: Exploring Dynamic Biospatial Networks with Mosaic Matrices and Mirror Glyphs

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

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