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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | VISOR: Visualizing Summaries of Ordered Data |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| ISBN | 978-1-4503-5282-6 |
| Page Range | 40:1 - 40:5 |
| Event Title | 29th International Conference on Scientific and Statistical Database Management |
| Event Type | conference |
| Event Location | Chicago, Illinois, USA |
| Event Start Date | June 27 - 2017 |
| Event End Date | June 29 - 2017 |
| Publisher | ACM |
| Abstract Text | In this paper, we present the VISOR tool, which helps the user to explore data and their summary structures by visualizing the relationships between the size k of a data summary and the induced error. Given an ordered dataset, VISOR allows to vary the size k of a data summary and to immediately see the effect on the induced error, by visualizing the error and its dependency on k in an &epsis;-graph and Δ-graph, respectively. The user can easily explore different values of k and determine the best value for the summary size. VISOR allows also to compare different summarization methods, such as piecewise constant approximation, piecewise aggregation approximation or V-optimal histograms. We show several demonstration scenarios, including how to determine an appropriate value for the summary size and comparing different summarization techniques. |
| Digital Object Identifier | 10.1145/3085504.3091115 |
| Other Identification Number | merlin-id:15012 |
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