%0 Conference Paper %1 10.1145/3517031.3531165 %A Rodrigues, Nils %A Shao, Lin %A Yan, Jia Jun %A Schreck, Tobias %A Weiskopf, Daniel %B 2022 Symposium on Eye Tracking Research and Applications %C New York, NY, USA %D 2022 %I Association for Computing Machinery %K visus:weiskopf b01 sfbtrr161 from:christinawarren visus:rodrigns 2022 visus %P 59:1-59:7 %R 10.1145/3517031.3531165 %T Eye Gaze on Scatterplot: Concept and First Results of Recommendations for Exploration of SPLOMs Using Implicit Data Selection %U https://doi.org/10.1145/3517031.3531165 %X We propose a three-step concept and visual design for supporting the visual exploration of high-dimensional data in scatterplots through eye-tracking. First, we extract subsets in the underlying data using existing classifications, automated clustering algorithms, or eye-tracking. For the latter, we map gaze to the underlying data dimensions in the scatterplot. Clusters of data points that have been the focus of the viewers’ gaze are marked as clusters of interest (eye-mind hypothesis). In a second step, our concept extracts various properties from statistics and scagnostics from the clusters. The third step uses these measures to compare the current data clusters from the main scatterplot to the same data in other dimensions. The results enable analysts to retrieve similar or dissimilar views as guidance to explore the entire data set. We provide a proof-of-concept implementation as a test bench and describe a use case to show a practical application and initial results. %@ 9781450392525

@inproceedings{10.1145/3517031.3531165, abstract = {We propose a three-step concept and visual design for supporting the visual exploration of high-dimensional data in scatterplots through eye-tracking. First, we extract subsets in the underlying data using existing classifications, automated clustering algorithms, or eye-tracking. For the latter, we map gaze to the underlying data dimensions in the scatterplot. Clusters of data points that have been the focus of the viewers’ gaze are marked as clusters of interest (eye-mind hypothesis). In a second step, our concept extracts various properties from statistics and scagnostics from the clusters. The third step uses these measures to compare the current data clusters from the main scatterplot to the same data in other dimensions. The results enable analysts to retrieve similar or dissimilar views as guidance to explore the entire data set. We provide a proof-of-concept implementation as a test bench and describe a use case to show a practical application and initial results.}, added-at = {2022-12-04T14:08:13.000+0100}, address = {New York, NY, USA}, articleno = {59}, author = {Rodrigues, Nils and Shao, Lin and Yan, Jia Jun and Schreck, Tobias and Weiskopf, Daniel}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2ac37ffb834154ebb5ff50954242e334a/visus}, booktitle = {2022 Symposium on Eye Tracking Research and Applications}, doi = {10.1145/3517031.3531165}, interhash = {ce94fb440175f7f20d7ee48dc3bd4ab9}, intrahash = {ac37ffb834154ebb5ff50954242e334a}, isbn = {9781450392525}, keywords = {visus:weiskopf b01 sfbtrr161 from:christinawarren visus:rodrigns 2022 visus}, location = {Seattle, WA, USA}, numpages = {7}, pages = {59:1-59:7}, publisher = {Association for Computing Machinery}, series = {ETRA '22}, timestamp = {2022-12-04T13:08:13.000+0100}, title = {Eye Gaze on Scatterplot: Concept and First Results of Recommendations for Exploration of SPLOMs Using Implicit Data Selection}, url = {https://doi.org/10.1145/3517031.3531165}, year = 2022 }