The Relationship Between Data Visualization and Task Performance Metadata

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Title

  • Main Title The Relationship Between Data Visualization and Task Performance

Creator

  • Author: Phillips, Brandon
    Creator Type: Personal

Contributor

  • Chair: Peak, Daniel Alan
    Contributor Type: Personal
    Contributor Info: Major Professor
  • Committee Member: Prybutok, Victor Ronald, 1952-
    Contributor Type: Personal
  • Committee Member: Blankson, Charles
    Contributor Type: Personal

Publisher

  • Name: University of North Texas
    Place of Publication: Denton, Texas
    Additional Info: www.unt.edu

Date

  • Creation: 2014-12

Language

  • English

Description

  • Content Description: We are entering an era of business intelligence and big data where simple tables and other traditional means of data display cannot deal with the vast amounts of data required to meet the decision-making needs of businesses and their clients. Graphical figures constructed with modern visualization software can convey more information than a table because there is a limit to the table size that is visually usable. Contemporary decision performance is influenced by the task domain, the user experience, and the visualizations themselves. Utilizing data visualization in task performance to aid in decision making is a complex process. We develop and test a decision-making framework to examine task performance in a visual and non-visual aided decision-making by using three experiments to test this framework. Studies 1 and 2 investigate DV formats and how complexity and design affects the proposed visual decision making framework. The studies also examine how DV formats affect task performance, as measured by accuracy and timeliness, and format preference. Additionally, these studies examine how DV formats influence the constructs in the proposed decision making framework which include information usefulness, decision confidence, cognitive load, visual aesthetics, information seeking intention, and emotion. Preliminary findings indicate that graphical DV allows individuals to respond faster and more accurately, resulting in improved task fit and performance. Anticipated implications of this research are as follows. Visualizations are independent of the size of the data set but can be increasingly complex as the data complexity increases. Furthermore, well designed visualizations let you see through the complexity and simultaneously mine the complexity with drill down technologies such as OLAP.
  • Physical Description: viii, 97 pages : illustrations (chiefly color)

Subject

  • Keyword: Task performance
  • Keyword: data visualization
  • Keyword: decision making
  • Library of Congress Subject Headings: Information visualization.
  • Library of Congress Subject Headings: Task analysis.
  • Library of Congress Subject Headings: Decision making.
  • Library of Congress Subject Headings: Business intelligence.

Collection

  • Name: UNT Theses and Dissertations
    Code: UNTETD

Institution

  • Name: UNT Libraries
    Code: UNT

Rights

  • Rights Access: public
  • Rights Holder: Phillips, Brandon
  • Rights License: copyright
  • Rights Statement: Copyright is held by the author, unless otherwise noted. All rights reserved.

Resource Type

  • Thesis or Dissertation

Format

  • Text

Identifier

  • Archival Resource Key: ark:/67531/metadc699897

Degree

  • Academic Department: Department of Information Technology and Decision Sciences
  • Degree Discipline: Business Computer Information Systems
  • Degree Level: Doctoral
  • Degree Name: Doctor of Philosophy
  • Degree Grantor: University of North Texas
  • Degree Publication Type: disse

Note