Towards a scripting language for visual data exploration

Visualization of data is becoming increasingly important for data analysis; numerous insights can be derived from visualizations at a glance. While the information provided through visualization is powerful, the visual analysis process remains largely manual, consuming valuable man-hours. Zenvisage automates the search for desired visual patterns, speeding up visual exploration. It does so through a query language, ZQL, that encapsulates the key data analysis operations such as comparison, sorting, filtering, and composition. However, Zenvisage is somewhat lacking in support for expert data analysts, who are comfortable with programming in existing data analytics tools and may not want to switch to a new system. In order to bring our tool to such users, we propose the Zenvisage Scripting Language, which the power of provides the same expressive power as ZQL but also integrates directly into an expert user’s programming language (in our case, we use ggplot and R as a case study). This would allow users to easily adapt their workflows to support visual exploration-based insight

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Xue, Edward H.

Contributors dc:contributor

• Parameswaran, Aditya G.

• Data Analytics
• Visual Data Analytics
• Automatic Visualization
• Databases
• Scripting Language
• R
• ggplot
• Data Exploration
• Zenvisage
• Query Language
• ZQL
• ZSL
• Data Science
• grammar
• CFG
• BNF

Statement dc:rights

• Copyright 2018 Edward Xue

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/101040

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/101040