%0 Journal Article %1 ISI:000364043400011 %A Blascheck, Tanja %A John, Markus %A Kurzhals, Kuno %A Koch, Steffen %A Ertl, Thomas %C 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA %D 2016 %I IEEE COMPUTER SOC %J IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS %K aloud; analytics; data} evaluation; eye interaction logs; qualitative series thinking time tracking; {visual %N 1 %P 61-70 %R 10.1109/TVCG.2015.2467871 %T VA(2): A Visual Analytics Approach for // Evaluating Visual Analytics Applications %V 22 %X Evaluation has become a fundamental part of visualization research and researchers have employed many approaches from the field of human-computer interaction like measures of task performance, thinking aloud protocols, and analysis of interaction logs. Recently, eye tracking has also become popular to analyze visual strategies of users in this context. This has added another modality and more data, which requires special visualization techniques to analyze this data. However, only few approaches exist that aim at an integrated analysis of multiple concurrent evaluation procedures. The variety, complexity, and sheer amount of such coupled multi-source data streams require a visual analytics approach. Our approach provides a highly interactive visualization environment to display and analyze thinking aloud, interaction, and eye movement data in close relation. Automatic pattern finding algorithms allow an efficient exploratory search and support the reasoning process to derive common eye-interaction-thinking patterns between participants. In addition, our tool equips researchers with mechanisms for searching and verifying expected usage patterns. We apply our approach to a user study involving a visual analytics application and we discuss insights gained from this joint analysis. We anticipate our approach to be applicable to other combinations of evaluation techniques and a broad class of visualization applications.

@article{ISI:000364043400011, abstract = {{Evaluation has become a fundamental part of visualization research and researchers have employed many approaches from the field of human-computer interaction like measures of task performance, thinking aloud protocols, and analysis of interaction logs. Recently, eye tracking has also become popular to analyze visual strategies of users in this context. This has added another modality and more data, which requires special visualization techniques to analyze this data. However, only few approaches exist that aim at an integrated analysis of multiple concurrent evaluation procedures. The variety, complexity, and sheer amount of such coupled multi-source data streams require a visual analytics approach. Our approach provides a highly interactive visualization environment to display and analyze thinking aloud, interaction, and eye movement data in close relation. Automatic pattern finding algorithms allow an efficient exploratory search and support the reasoning process to derive common eye-interaction-thinking patterns between participants. In addition, our tool equips researchers with mechanisms for searching and verifying expected usage patterns. We apply our approach to a user study involving a visual analytics application and we discuss insights gained from this joint analysis. We anticipate our approach to be applicable to other combinations of evaluation techniques and a broad class of visualization applications.}}, added-at = {2017-05-18T11:32:12.000+0200}, address = {{10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA}}, affiliation = {{Blascheck, T (Reprint Author), Univ Stuttgart, Inst Visualizat \& Interact Syst VIS, Stuttgart, Germany. Kurzhals, Kuno, Univ Stuttgart, Visualizat Res Ctr, Stuttgart, Germany. Blascheck, Tanja; John, Markus; Koch, Steffen; Ertl, Thomas, Univ Stuttgart, Inst Visualizat \& Interact Syst VIS, Stuttgart, Germany.}}, author = {Blascheck, Tanja and John, Markus and Kurzhals, Kuno and Koch, Steffen and Ertl, Thomas}, author-email = {{tanja.blascheck@vis.uni-stuttgart.de markus.john@vis.uni-stuttgart.de kuno.kurzhals@virus.uni-stuttgart.de steffen.koch@vis.uni-stuttgart.de thomas.ertl@vis.uni-stuttgart.de}}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2cc131f8c378577ab621d7a274ca4c61d/hermann}, doi = {{10.1109/TVCG.2015.2467871}}, eissn = {{1941-0506}}, funding-acknowledgement = {{German Federal Ministry of Education and Research (BMBF); German Science Foundation (DFG) {[}(SPP) 1335]}}, funding-text = {{This work has been partially funded by the German Federal Ministry of Education and Research (BMBF) as part of the `ePoetics' project and the German Science Foundation (DFG) as part of the priority program (SPP) 1335 `Scalable Visual Analytics'.}}, interhash = {5effcc98e8efb3870ffb9ba9a527edfb}, intrahash = {cc131f8c378577ab621d7a274ca4c61d}, issn = {{1077-2626}}, journal = {{IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS}}, keywords = {aloud; analytics; data} evaluation; eye interaction logs; qualitative series thinking time tracking; {visual}, keywords-plus = {{EYE FIXATIONS; VISUALIZATION; INSIGHT; METHODOLOGY; MOVEMENT; SEARCH; TOOL}}, language = {{English}}, month = {{JAN}}, note = {{10th IEEE Conference on Visual Analytics Science and Technology (VAST) / IEEE VIS Conference, Chicago, IL, OCT 25-30, 2015}}, number = {{1}}, number-of-cited-references = {{52}}, organization = {{IEEE; IEEE Comp Soc; IEEE Visualizat and Graph Tech Comm; InfoVis; SciVis}}, pages = {{61-70}}, publisher = {{IEEE COMPUTER SOC}}, research-areas = {{Computer Science}}, times-cited = {{4}}, timestamp = {2017-05-18T09:32:12.000+0200}, title = {{VA(2): A Visual Analytics Approach for // Evaluating Visual Analytics Applications}}, type = {{Article; Proceedings Paper}}, volume = {{22}}, web-of-science-categories = {{Computer Science, Software Engineering}}, year = {{2016}} }