Visualization schemas and a web-based architecture for custom multiple-view visualization of multiple-table databases

  • Authors:

  • Chris North;Nathan Conklin;Kiran Indukuri;Varun Saini

  • Affiliations:

  • Center for Human-Computer Interaction, Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia;Center for Human-Computer Interaction, Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia;Center for Human-Computer Interaction, Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia;Center for Human-Computer Interaction, Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, Virginia

  • Venue:
  • Information Visualization
  • Year:
  • 2002

Quantified Score

Hi-index 0.00

Visualization

Abstract

Relational databases provide significant flexibility to organize, store, and manipulate an infinite variety of complex data collections. This flexibility is enabled by the concept of relational data schemas, which allow data owners to easily design custom databases according to their unique needs. However, user interfaces and information visualizations for accessing and utilizing databases have not kept pace with this level of flexibility. Visualizations need to integrate multiple tables and diverse visualization tools into custom solutions. This paper describes advances to Snap-Together Visualization, introduces Visualization Schemas, and presents an extensible system architecture. The Snap model for custom multiple-view visualization establishes an analogy to the relational data model, enabling coordinated data design and visualization design. Visualization Schemas are a natural extension to data schemas, and provide a user interface that enables data owners to rapidly construct and disseminate custom visualizations without programming. The web-based software architecture supports run-time extensibility, enabling end-user integration and dissemination of diverse data and visualization tools from the field.