Effortless data exploration with zenvisage: an expressive and interactive visual analytics system

Siddiqui, Tarique Ashraf

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https://hdl.handle.net/2142/92826 Copy

Description

Title

Effortless data exploration with zenvisage: an expressive and interactive visual analytics system

Author(s)

Siddiqui, Tarique Ashraf

Issue Date

2016-07-14

Director of Research (if dissertation) or Advisor (if thesis)

• Parameswaran, Aditya G.
• Han, Jiawei

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Visual analytics
• Databases
• Query language
• Visualization

Abstract

"Data visualization is by far the most commonly used mechanism to explore data, especially by novice data analysts and data scientists. And yet, current visual analytics tools are rather limited in their ability to guide data scientists to interesting or desired visualizations: the process of visual data exploration remains cumbersome and time-consuming. We propose zenvisage, a platform for effortlessly visualizing interesting patterns, trends, or insights from large datasets. We describe zenvisage's general purpose visual query language, ZQL (""zee-quel"") for specifying the desired visual trend, pattern, or insight — ZQL draws from use-cases in a variety of domains, including biology, mechanical engineering, climate science, and commerce. We formalize the expressiveness of ZQL via a visual exploration algebra, and demonstrate that ZQL is at least as expressive as that algebra. While analysts are free to use ZQL directly, we also expose ZQL via a visual specification interface. We then describe our architecture and optimizations, preliminary experiments in supporting and optimizing for ZQL queries in our initial zenvisage prototype, and a user study to evaluate whether data scientists are able to effectively use zenvisage for real applications."

Graduation Semester

2016-08

Type of Resource

text

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http://hdl.handle.net/2142/92826

Copyright and License Information

Copyright 2016 Tarique Ashraf Siddiqui

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