ShapeSearch: Flexible patternbased querying of trend line visualizations

Tarique Siddiqui, Paul Luh, Zesheng Wang, Karrie Karahalios, Aditya Parameswaran

Research output: Contribution to journalConference articlepeer-review


Finding visualizations with desired patterns is a common goal during data exploration. However, due to the limited expressiveness and flexibility of existing visual analytics systems, pattern-based querying of visualizations has largely been a manual process. We demonstrate ShapeSearch, a system that enables users to express their desired patterns in trend lines using multiple flexible mechanisms - including natural language and visual regular expressions, and automates the search via an optimized execution engine. Internally, the system leverages an expressive shape query algebra that supports a range of operators and primitives for representing ShapeSearch queries. In our demonstration, conference attendees will learn how the various components of ShapeSearch help accelerate scientific discovery by automating the search for meaningful patterns in trend lines in domains such as genomics and material science.

Original languageEnglish (US)
Pages (from-to)1962-1965
Number of pages4
JournalProceedings of the VLDB Endowment
Issue number12
StatePublished - 2018
Event44th International Conference on Very Large Data Bases, VLDB 2018 - Rio de Janeiro, Brazil
Duration: Aug 27 2018Aug 31 2018

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • General Computer Science


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