Vis4Vis: Visualization for (Empirical) Visualization Research

Weiskopf, Daniel

doi:10.1007/978-3-030-34444-3_10

Cited by 4 publications

(2 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is challenging to integrate data from heterogeneous data sources, such as eye tracking and other physiological sensors, as well as hand-written or verbal protocols. An interesting approach toward these problems is visual data analysis, sometimes referred to as visualization for visualization (Vis4Vis) [42]. The vision behind Vis4Vis is to use visualizations to analyze and communicate data from empirical studies.…”

Section: Interpretation and Data Analysismentioning

confidence: 99%

Visualization Psychology for Eye Tracking Evaluation

Koch¹,

Kurzhals²,

Burch³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Technical progress in hardware and software enables us to record gaze data in everyday situations and over long time spans. Among a multitude of research opportunities, this technology enables visualization researchers to catch a glimpse behind performance measures and into the perceptual and cognitive processes of people using visualization techniques. The majority of eye tracking studies performed for visualization research is limited to the analysis of gaze distributions and aggregated statistics, thus only covering a small portion of insights that can be derived from gaze data. We argue that incorporating theories and methodology from psychology and cognitive science will benefit the design and evaluation of eye tracking experiments for visualization. This book chapter provides an overview of how eye tracking can be used in a variety of study designs. Further, we discuss the potential merits of cognitive models for the evaluation of visualizations. We exemplify these concepts on two scenarios, each focusing on a different eye tracking study. Lastly, we identify several call for actions.

show abstract

Section: Interpretation and Data Analysismentioning

confidence: 99%

Visualization Psychology for Eye Tracking Evaluation

Koch¹,

Kurzhals²,

Burch³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Data visualization interfaces that aim to support the user in understanding complex, interconnected data are commonly used in visual analytics (Keim et al, 2008;Weiskopf, 2019) and e-learning (Silva et al, The version of record is available at: http://dx.doi.org/10.1561/1500000073 2019). Eye gaze data, together with search behavior data or user characteristics, can be used to infer types of search tasks (Steichen et al, 2014).…”

Section: Data Visualization Interfaces In Virtual Environmentsmentioning

confidence: 99%

Search Interface Design and Evaluation

Liu

et al. 2021

FNT in Information Retrieval

View full text Add to dashboard Cite

This monograph reviews research on the design and evaluation of search user interfaces that has been published within the past 10 years. Our primary goal is to integrate state-of-the-art research in the areas of information seeking behavior, information retrieval, and human-computer interaction on the topic of search interface. Specifically, this monograph (1) describes the history and background of the development of the search interface; (2) introduces information search behavior models that help conceptualize users' information needs, and how people seek, select, and use information; (3) characterizes the major components of search interfaces that support different subprocesses based on Marchonini's information seeking process model; (4) reviews the design of search interfaces for different user groups, especially that of vulnerable people, as well as personalized and adaptive search interfaces; (5) identifies evaluation methods of search interfaces and how they were implemented in research having different evaluation purposes. We also provide an outlook on the future trends of search interfaces including

show abstract

Bridging Quantitative and Qualitative Methods for Visualization Research: A Data/Semantics Perspective in Light of Advanced AI

Weiskopf

2024

2024 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)

View full text Add to dashboard Cite

Vis4Vis: Visualization for (Empirical) Visualization Research

Cited by 4 publications

References 64 publications

Visualization Psychology for Eye Tracking Evaluation

Visualization Psychology for Eye Tracking Evaluation

Search Interface Design and Evaluation

Bridging Quantitative and Qualitative Methods for Visualization Research: A Data/Semantics Perspective in Light of Advanced AI

Contact Info

Product

Resources

About