dc.contributor.author | Eckelt, Klaus | en_US |
dc.contributor.author | Adelberger, Patrick | en_US |
dc.contributor.author | Zichner, Thomas | en_US |
dc.contributor.author | Wernitznig, Andreas | en_US |
dc.contributor.author | Streit, Marc | en_US |
dc.contributor.editor | Landesberger, Tatiana von and Turkay, Cagatay | en_US |
dc.date.accessioned | 2019-06-02T18:19:19Z | |
dc.date.available | 2019-06-02T18:19:19Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 978-3-03868-087-1 | |
dc.identifier.uri | https://doi.org/10.2312/eurova.20191117 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/eurova20191117 | |
dc.description.abstract | Seeking relationships and patterns in tabular data is a common data exploration task. To confirm hypotheses that are based on visual patterns observed during exploratory data analysis, users need to be able to quickly compare data subsets, and get further information on the significance of the result and the statistical test applied. Existing tools, however, either focus on the comparison of a single data type, such as comparing numerical attributes only, or provide little or no statistical evaluation to assess a hypothesis. To fill this gap, we present TourDino, a support view that helps users who are not experts in statistics to verify generated hypotheses and confirm insights gained during the exploration of tabular data. In TourDino we present an overview of the statistical significance of various row or column comparisons. On demand, we show further details, including the test score, a textual description, and a detail visualization explaining the results. To demonstrate the efficacy of our approach, we have integrated TourDino in the Ordino drug discovery platform for the purpose of identifying new drug targets. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.title | TourDino: A Support View for Confirming Patterns in Tabular Data | en_US |
dc.description.seriesinformation | EuroVis Workshop on Visual Analytics (EuroVA) | |
dc.description.sectionheaders | Visual Analytics Methods | |
dc.identifier.doi | 10.2312/eurova.20191117 | |
dc.identifier.pages | 7-11 | |