VisTrails: Visualization meets data management

Steven P. Callahan, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Cláudio T. Silva, Huy T. Vo

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Scientists are now faced with an incredible volume of data to analyze. To successfully analyze and validate various hypothesis, it is necessary to pose several queries, correlate disparate data, and create insightful visualizations of both the simulated processes and observed phenomena. Often, insight comes from comparing the results of multiple visualizations. Unfortunately, today this process is far from interactive and contains many error-prone and time-consuming tasks. As a result, the generation and maintenance of visualizations is a major bottleneck in the scientific process, hindering both the ability to mine scientific data and the actual use of the data. The VisTrails system represents our initial attempt to improve the scientific discovery process and reduce the time to insight. In VisTrails, we address the problem of visualization from a data management perspective: VisTrails manages the data and metadata of a visualization product. In this demonstration, we show the power and flexibility of our system by presenting actual scenarios in which scientific visualization is used and showing how our system improves usability, enables reproducibility, and greatly reduces the time required to create scientific visualizations.

Original languageEnglish (US)
Title of host publicationSIGMOD 2006 - Proceedings of the ACM SIGMOD International Conference on Management of Data
Number of pages3
StatePublished - 2006
Event2006 ACM SIGMOD International Conference on Management of Data - Chicago, IL, United States
Duration: Jun 27 2006Jun 29 2006

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078


Other2006 ACM SIGMOD International Conference on Management of Data
Country/TerritoryUnited States
CityChicago, IL


  • Data provenance
  • Scientific dataflows
  • Visualization

ASJC Scopus subject areas

  • Software
  • Information Systems


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