OnSet: A Visualization Technique for Large-scale Binary Set Data

Sadana, Ramik; Major, Timothy; Dove, Alistair D. M.; Stasko, John

doi:10.1109/tvcg.2014.2346249

Cited by 63 publications

(47 citation statements)

References 25 publications

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“…Recently, Sadana et al [SMDS14] proposed a technique that superposes representations of sets to compare which elements are common across sets. A pile is meant to visually aggregate selections of information rather than just organizing objects.…”

Section: The Piling Metaphormentioning

confidence: 99%

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Small MultiPiles: Piling Time to Explore Temporal Patterns in Dynamic Networks

Bach

Henry-Riche

Dwyer

et al. 2015

Computer Graphics Forum

100

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International audienceWe introduce MultiPiles, a visualization to explore time-series of dense, weighted networks. MultiPiles is based on the physical analogy of piling adjacency matrices, each one representing a single temporal snapshot. Common interfaces for visualizing dynamic networks use techniques such as: flipping/animation; small multiples; or summary views in isolation. Our proposed 'piling' metaphor presents a hybrid of these techniques, leveraging each one's advantages, as well as offering the ability to scale to networks with hundreds of temporal snapshots. While the MultiPiles technique is applicable to many domains, our prototype was initially designed to help neuroscien-tists investigate changes in brain connectivity networks over several hundred snapshots. The piling metaphor and associated interaction and visual encodings allowed neuroscientists to explore their data, prior to a statistical analysis. They detected high-level temporal patterns in individual networks and this helped them to formulate and reject several hypotheses

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Section: The Piling Metaphormentioning

confidence: 99%

“…A pile is meant to visually aggregate selections of information rather than just organizing objects. Recently, Sadana et al [SMDS14] proposed a technique that superposes representations of sets to compare which elements are common across sets. Their MultiLayers are formed by direct manipulation using drag and drop.…”

Section: The Piling Metaphormentioning

confidence: 99%

Small MultiPiles: Piling Time to Explore Temporal Patterns in Dynamic Networks

Bach

Henry-Riche

Dwyer

et al. 2015

Computer Graphics Forum

100

View full text Add to dashboard Cite

show abstract

“…OnSet [31] is a space-filling visualization of binary set data that supports comparison between and combination of sets, and scales to several hundred elements per set. Gleicher et al [15] have presented a general survey on comparative visualization.…”

Section: Related Workmentioning

confidence: 99%

NeuroBlocks – Visual Tracking of Segmentation and Proofreading for Large Connectomics Projects

Ai-Awami

Beyer

Haehn

et al. 2016

IEEE Trans. Visual. Comput. Graphics

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In the field of connectomics, neuroscientists acquire electron microscopy volumes at nanometer resolution in order to reconstruct a detailed wiring diagram of the neurons in the brain. The resulting image volumes, which often are hundreds of terabytes in size, need to be segmented to identify cell boundaries, synapses, and important cell organelles. However, the segmentation process of a single volume is very complex, time-intensive, and usually performed using a diverse set of tools and many users. To tackle the associated challenges, this paper presents NeuroBlocks, which is a novel visualization system for tracking the state, progress, and evolution of very large volumetric segmentation data in neuroscience. NeuroBlocks is a multi-user web-based application that seamlessly integrates the diverse set of tools that neuroscientists currently use for manual and semi-automatic segmentation, proofreading, visualization, and analysis. NeuroBlocks is the first system that integrates this heterogeneous tool set, providing crucial support for the management, provenance, accountability, and auditing of large-scale segmentations. We describe the design of NeuroBlocks, starting with an analysis of the domain-specific tasks, their inherent challenges, and our subsequent task abstraction and visual representation. We demonstrate the utility of our design based on two case studies that focus on different user roles and their respective requirements for performing and tracking the progress of segmentation and proofreading in a large real-world connectomics project.

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“…Other systems, such as Dust and Magnet [36] and Kinetica [22], represent data cases as physical objects that can be dragged and pushed to expose their underlying attributes. Furthermore, interaction can be used to implement semantic operations within a domain, such as the OnSet system's use of drag-and-drop style interaction to perform union and intersection operations on set-typed data [23].…”

Section: The Importance Of Interactionmentioning

confidence: 99%

Value-driven evaluation of visualizations

Stasko

2014

Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization

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Existing evaluations of data visualizations often employ a series of low-level, detailed questions to be answered or benchmark tasks to be performed. While that methodology can be helpful to determine a visualization's usability, such evaluations overlook the key benefits that visualization uniquely provides over other data analysis methods. I propose a value-driven evaluation of visualizations in which a person illustrates a system's value through four important capabilities: minimizing the time to answer diverse questions, spurring the generation of insights and insightful questions, conveying the essence of the data, and generating confidence and knowledge about the data's domain and context. Additionally, I explain how interaction is instrumental in creating much of the value that can be found in visualizations.

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OnSet: A Visualization Technique for Large-scale Binary Set Data

Cited by 63 publications

References 25 publications

Small MultiPiles: Piling Time to Explore Temporal Patterns in Dynamic Networks

Small MultiPiles: Piling Time to Explore Temporal Patterns in Dynamic Networks

NeuroBlocks – Visual Tracking of Segmentation and Proofreading for Large Connectomics Projects

Value-driven evaluation of visualizations

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