CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Design galleries: a general approach to setting parameters for computer graphics and animation
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
A spreadsheet interface for visualization exploration
Proceedings of the conference on Visualization '00
Visualization Exploration and Encapsulation via a Spreadsheet-Like Interface
IEEE Transactions on Visualization and Computer Graphics
Polaris: A System for Query, Analysis, and Visualization of Multidimensional Relational Databases
IEEE Transactions on Visualization and Computer Graphics
Principles for Information Visualization Spreadsheets
IEEE Computer Graphics and Applications
Deploying Web-Based Visual Exploration Tools on the Grid
IEEE Computer Graphics and Applications
Multiscale Visualization Using Data Cubes
IEEE Transactions on Visualization and Computer Graphics
A spreadsheet approach to information visualization
INFOVIS '97 Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)
Multiscale Visualization Using Data Cubes "InfoVis 2002 Best Paper"
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
A problem-oriented classification of visualization techniques
VIS '90 Proceedings of the 1st conference on Visualization '90
A Spreadsheet Framework for Visual Exploration of Biomedical Datasets
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
Semiology of graphics
Low-Level Components of Analytic Activity in Information Visualization
INFOVIS '05 Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization
VisTrails: visualization meets data management
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
A Visualization System for Space-Time and Multivariate Patterns (VIS-STAMP)
IEEE Transactions on Visualization and Computer Graphics
Toward a Deeper Understanding of the Role of Interaction in Information Visualization
IEEE Transactions on Visualization and Computer Graphics
Tackling the Provenance Challenge one layer at a time
Concurrency and Computation: Practice & Experience - The First Provenance Challenge
Supporting the analytical reasoning process in information visualization
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Graphical Histories for Visualization: Supporting Analysis, Communication, and Evaluation
IEEE Transactions on Visualization and Computer Graphics
An integrated approach for visual analysis of a multisource moving objects knowledge base
International Journal of Geographical Information Science - Geospatial Visual Analytics: Focus on Time Special Issue of the ICA Commission on GeoVisualization
Preparing, Exploring and Comparing Cancer Simulation Results within a Large Parameter Space
IV '10 Proceedings of the 2010 14th International Conference Information Visualisation
Exploring high-D spaces with multiform matrices and small multiples
INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization
Provenance-Enabled Data Exploration and Visualization with VisTrails
SIBGRAPI-T '10 Proceedings of the 2010 23RD SIBGRAPI - Conference on Graphics, Patterns and Images Tutorials
Interactive dynamics for visual analysis
Communications of the ACM
| Hi-index | 0.00 |
We present a novel visual exploration method based on small multiples and large singles for effective and efficient data analysis. Users are enabled to explore the state space by offering multiple alternatives from the current state. Users can then select the alternative of choice and continue the analysis. Furthermore, the intermediate steps in the exploration process are preserved and can be revisited and adapted using an intuitive navigation mechanism based on the well-known undo-redo stack and filmstrip metaphor. As proof of concept the exploration method is implemented in a prototype. The effectiveness of the exploration method is tested using a formal user study comparing four different interaction methods. By using Small Multiples as data exploration method users need fewer steps in answering questions and also explore a significantly larger part of the state space in the same amount of time, providing them with a broader perspective on the data, hence lowering the chance of missing important features. Also, users prefer visual exploration with small multiples over non-small multiple variants.