%0 Journal Article %1 lam2012empirical %A Lam, Heidi %A Bertini, Enrico %A Isenberg, Petra %A Plaisant, Catherine %A Carpendale, Sheelagh %D 2012 %J IEEE Transactions on Visualization and Computer Graphics %K evaluation userstudies visualization %N 9 %P 1520-1536 %R 10.1109/TVCG.2011.279 %T Empirical Studies in Information Visualization: Seven Scenarios %U https://ieeexplore.ieee.org/document/6095544 %V 18 %X We take a new, scenario-based look at evaluation in information visualization. Our seven scenarios, evaluating visual data analysis and reasoning, evaluating user performance, evaluating user experience, evaluating environments and work practices, evaluating communication through visualization, evaluating visualization algorithms, and evaluating collaborative data analysis were derived through an extensive literature review of over 800 visualization publications. These scenarios distinguish different study goals and types of research questions and are illustrated through example studies. Through this broad survey and the distillation of these scenarios, we make two contributions. One, we encapsulate the current practices in the information visualization research community and, two, we provide a different approach to reaching decisions about what might be the most effective evaluation of a given information visualization. Scenarios can be used to choose appropriate research questions and goals and the provided examples can be consulted for guidance on how to design one's own study.

@article{lam2012empirical, abstract = {We take a new, scenario-based look at evaluation in information visualization. Our seven scenarios, evaluating visual data analysis and reasoning, evaluating user performance, evaluating user experience, evaluating environments and work practices, evaluating communication through visualization, evaluating visualization algorithms, and evaluating collaborative data analysis were derived through an extensive literature review of over 800 visualization publications. These scenarios distinguish different study goals and types of research questions and are illustrated through example studies. Through this broad survey and the distillation of these scenarios, we make two contributions. One, we encapsulate the current practices in the information visualization research community and, two, we provide a different approach to reaching decisions about what might be the most effective evaluation of a given information visualization. Scenarios can be used to choose appropriate research questions and goals and the provided examples can be consulted for guidance on how to design one's own study.}, added-at = {2022-02-21T14:01:24.000+0100}, author = {Lam, Heidi and Bertini, Enrico and Isenberg, Petra and Plaisant, Catherine and Carpendale, Sheelagh}, biburl = {https://www.bibsonomy.org/bibtex/243a543db4fcc0ff7a831743a10005699/abernstetter}, description = {Empirical Studies in Information Visualization: Seven Scenarios | IEEE Journals & Magazine | IEEE Xplore}, doi = {10.1109/TVCG.2011.279}, interhash = {5c1dfcb380356daac5892f7de62a2913}, intrahash = {43a543db4fcc0ff7a831743a10005699}, issn = {1941-0506}, journal = {IEEE Transactions on Visualization and Computer Graphics}, keywords = {evaluation userstudies visualization}, month = {Sep.}, number = 9, pages = {1520-1536}, timestamp = {2022-02-21T14:01:24.000+0100}, title = {Empirical Studies in Information Visualization: Seven Scenarios}, url = {https://ieeexplore.ieee.org/document/6095544}, volume = 18, year = 2012 }