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Interactive Dynamics for Visual Analysis: A taxonomy of tools that support the fluent and flexible use of visualizations

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Ben ShneidermanAuthors Info & Claims

Queue, Volume 10, Issue 2

Pages 30 - 55

https://doi.org/10.1145/2133416.2146416

Published: 01 February 2012 Publication History

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Abstract

The increasing scale and availability of digital data provides an extraordinary resource for informing public policy, scientific discovery, business strategy, and even our personal lives. To get the most out of such data, however, users must be able to make sense of it: to pursue questions, uncover patterns of interest, and identify (and potentially correct) errors. In concert with data-management systems and statistical algorithms, analysis requires contextualized human judgments regarding the domain-specific significance of the clusters, trends, and outliers discovered in data.

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Index Terms

Interactive Dynamics for Visual Analysis: A taxonomy of tools that support the fluent and flexible use of visualizations
1. Human-centered computing
  1. Human computer interaction (HCI)

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Queue

Queue Volume 10, Issue 2

Micoprocessors

February 2012

42 pages

ISSN:1542-7730

EISSN:1542-7749

DOI:10.1145/2133416

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Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 February 2012

Published in QUEUE Volume 10, Issue 2

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https://doi.org/10.46925//rdluz.43.19
Che HLu TCai SLi MLu W(2024)Inverse Design of Low-Resistivity Ternary Gold Alloys via Interpretable Machine Learning and Proactive Search ProgressMaterials10.3390/ma1714361417:14(3614)Online publication date: 22-Jul-2024
https://doi.org/10.3390/ma17143614
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