Xinyi Zhou 0005

dblp:183/6661-5 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 67% Multimedia systems and quality of experience · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Multimedia systems and quality of experience › user interaction
interaction techniques and input
0.512021
A Generic Framework and Library for Exploration of Small Multiples through Interactive Piling · IEEE Trans. Vis. Comput. Graph. 2021
Visualization and visual analytics › multi-view visualization
small multiples
0.512021
A Generic Framework and Library for Exploration of Small Multiples through Interactive Piling · IEEE Trans. Vis. Comput. Graph. 2021
Visualization and visual analytics › interaction design
user interface design and tools
0.512021
A Generic Framework and Library for Exploration of Small Multiples through Interactive Piling · IEEE Trans. Vis. Comput. Graph. 2021

Methods — techniques the papers use, named apart from their topics

declarative interface design · 0.5
YearPublicationVenuePosition
2021 A Generic Framework and Library for Exploration of Small Multiples through Interactive Piling
abstract
Small multiples are miniature representations of visual information used generically across many domains. Handling large numbers of small multiples imposes challenges on many analytic tasks like inspection, comparison, navigation, or annotation. To address these challenges, we developed a framework and implemented a library called PILlNG.JS for designing interactive piling interfaces. Based on the piling metaphor, such interfaces afford flexible organization, exploration, and comparison of large numbers of small multiples by interactively aggregating visual objects into piles. Based on a systematic analysis of previous work, we present a structured design space to guide the design of visual piling interfaces. To enable designers to efficiently build their own visual piling interfaces, PILlNG.JS provides a declarative interface to avoid having to write low-level code and implements common aspects of the design space. An accompanying GUI additionally supports the dynamic configuration of the piling interface. We demonstrate the expressiveness of PILlNG.JS with examples from machine learning, immunofluorescence microscopy, genomics, and public health.
Fritz Lekschas, Xinyi Zhou 0005, Wei Chen 0001, Nils Gehlenborg, Benjamin Bach, Hanspeter Pfister
IEEE Trans. Vis. Comput. Graph.2