Dataopsy: Scalable and Fluid Visual Exploration using Aggregate Query Sculpting

TY - JOUR

T1 - Dataopsy

T2 - Scalable and Fluid Visual Exploration using Aggregate Query Sculpting

AU - Hoque, Md Naimul

AU - Elmqvist, Niklas

N1 - Publisher Copyright: © 1995-2012 IEEE.

PY - 2024/1/1

Y1 - 2024/1/1

N2 - 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 P6: 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 Dataopsy, 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.

AB - 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 P6: 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 Dataopsy, 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.

KW - Multidimensional data visualization

KW - multivariate graphs

KW - visual exploration

KW - visual queries

UR - https://www.scopus.com/pages/publications/85176339961

U2 - 10.1109/TVCG.2023.3326594

DO - 10.1109/TVCG.2023.3326594

M3 - Journal article

C2 - 37871052

AN - SCOPUS:85176339961

SN - 1077-2626

VL - 30

SP - 186

EP - 196

JO - IEEE Transactions on Visualization and Computer Graphics

JF - IEEE Transactions on Visualization and Computer Graphics

IS - 1

ER -