VisComplete: Automating suggestions for visualization pipelines

David Koop, Carlos E. Scheidegger, Steven P. Callahan, Juliana Freire, Cláudio T. Silva

Research output: Contribution to journalArticle

58 Scopus citations

Abstract

Building visualization and analysis pipelines is a large hurdle in the adoption of visualization and workflow systems by domain scientists. In this paper, we propose techniques to help users construct pipelines by consensus - automatically suggesting completions based on a database of previously created pipelines. In particular, we compute correspondences between existing pipeline subgraphs from the database, and use these to predict sets of likely pipeline additions to a given partial pipeline. By presenting these predictions in a carefully designed interface, users can create visualizations and other data products more efficiently because they can augment their normal work patterns with the suggested completions. We present an implementation of our technique in a publicly-available, open-source scientific workflow system and demonstrate efficiency gains in real-world situations.

Original languageEnglish (US)
Article number4658192
Pages (from-to)1691-1698
Number of pages8
JournalIEEE Transactions on Visualization and Computer Graphics
Volume14
Issue number6
DOIs
StatePublished - Nov 2008

Keywords

  • Auto completion
  • Scientific visualization
  • Scientific workflows

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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