Journal article
Dataopsy: Scalable and Fluid Visual Exploration using Aggregate Query Sculpting
IEEE transactions on visualization and computer graphics, Vol.30(1), pp.186-196
01/01/2024
DOI: 10.1109/TVCG.2023.3326594
PMID: 37871052
Abstract
We present aggregate query sculpting (AQS), a faceted visual query technique for large-scale multidimensional data. As a "born scalable" query technique, AQS starts visualization with a single visual mark representing an aggregation of the entire dataset. The user can then progressively explore the dataset through a sequence of operations abbreviated as <inline-formula><tex-math notation="LaTeX">\mathbb{P}^{6}</tex-math> <inline-graphic xlink:href="tvcg-hoque-3326594-eqinline-1-small.tif"/> </inline-formula>: pivot (facet an aggregate based on an attribute), partition (lay out a facet in space), peek (see inside a subset using an aggregate visual representation), pile (merge two or more subsets), project (extracting a subset into a new substrate), and prune (discard an aggregate not currently of interest). We validate AQS with D ataopsy , a prototype implementation of AQS that has been designed for fluid interaction on desktop and touch-based mobile devices. We demonstrate AQS and Dataopsy using two case studies and three application examples.
Details
- Title: Subtitle
- Dataopsy: Scalable and Fluid Visual Exploration using Aggregate Query Sculpting
- Creators
- Md Naimul Hoque - University of Maryland, College ParkNiklas Elmqvist - Aarhus University
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on visualization and computer graphics, Vol.30(1), pp.186-196
- Publisher
- IEEE
- DOI
- 10.1109/TVCG.2023.3326594
- PMID
- 37871052
- ISSN
- 1077-2626
- eISSN
- 1941-0506
- Number of pages
- 11
- Grant note
- 2211628 / U.S. National Science Foundation
- Language
- English
- Date published
- 01/01/2024
- Academic Unit
- Computer Science
- Record Identifier
- 9984787457802771
Metrics
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