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Roberta S. Russell

dblp:74/1375 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0003-3067-2679ORCID · corroborated

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

Artificial intelligence and machine learning · 1Security and privacy · 1Graphics, computer vision, multimedia, augmented reality and games · 1

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 · 100%
Human-computer interaction and pervasive computing
1 paper
Usability and user experience research · 100%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › visualization evaluation
information visualization evaluation		 0.112010
Using Cognitive Fit Theory to Evaluate the Effectiveness of Information Visualizations: An Example Using Quality Assurance Data · IEEE Trans. Vis. Comput. Graph. 2010

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

proximity compatibility principle · 0.2cognitive fit theory · 0.2
YearPublicationVenuePosition
2016 Decision support for long-range, community-based planning to mitigate against and recover from potential multiple disasters
Josey Chacko, Loren Paul Rees, Christopher W. Zobel, Terry R. Rakes, Roberta S. Russell, Cliff T. Ragsdale
 Decis. Support Syst.5
2013 The challenge and imperative of private sector cybersecurity: An international comparison
Janine S. Hiller, Roberta S. Russell
 Comput. Law Secur. Rev.2
2010 Using Cognitive Fit Theory to Evaluate the Effectiveness of Information Visualizations: An Example Using Quality Assurance Data
abstract
Cognitive fit theory, along with the proximity compatibility principle, is investigated as a basis to evaluate the effectiveness of information visualizations to support a decision-making task. The task used in this study manipulates varying levels of task complexity for quality control decisions in a high-volume discrete manufacturing environment. The volume of process monitoring and quality control data produced in this type of environment can be daunting. Today's managers need effective decision support tools to sort through the morass of data in a timely fashion to make critical decisions on product and process quality.
Jay M. Teets, David P. Tegarden, Roberta S. Russell
 IEEE Trans. Vis. Comput. Graph.3