XmdvtoolQ:: quality-aware interactive data exploration

Authors:
Elke A. Rundensteiner;Matthew O. Ward;Zaixian Xie;Qingguang Cui;Charudatta V. Wad;Di Yang;Shiping Huang
Affiliations:
Worcester Polytechnic Institute, Worcester, MA;Worcester Polytechnic Institute, Worcester, MA;Worcester Polytechnic Institute, Worcester, MA;Worcester Polytechnic Institute, Worcester, MA;Worcester Polytechnic Institute, Worcester, MA;Worcester Polytechnic Institute, Worcester, MA;Worcester Polytechnic Institute, Worcester, MA
Venue:
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Year:
2007

Citing 5
Cited 4

Structure-Based Brushes: A Mechanism for Navigating Hierarchically Organized Data and Information Spaces

IEEE Transactions on Visualization and Computer Graphics
Value and Relation Display for Interactive Exploration of High Dimensional Datasets

INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
Clutter Reduction in Multi-Dimensional Data Visualization Using Dimension Reordering

INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
A strategy selection framework for adaptive prefetching in data visualization

SSDBM '03 Proceedings of the 15th International Conference on Scientific and Statistical Database Management
Measuring Data Abstraction Quality in Multiresolution Visualizations

IEEE Transactions on Visualization and Computer Graphics

A salience-based quality metric for visualization

EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
The importance of tracing data through the visualization pipeline

Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors - Novel Evaluation Methods for Visualization
Hierarchical visual filtering, pragmatic and epistemic actions for database visualization

Proceedings of the 28th Annual ACM Symposium on Applied Computing
An information-theoretic observation channel for volume visualization

EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this work, we describe our approach for making the interactive data exploration system, called XmdvTool, quality-aware to assure informed decision-making. XmdvToolQ, makes quality or lack thereof explicit for all stages of the data exploration process from raw data, to abstracted data, to the final visual displays, allowing users to query and navigate through data-, structure- and quality-spaces.