Skip to content

GitLab

  • Projects
  • Groups
  • Snippets
  • Help
    • Loading...
  • Help
    • Help
    • Support
    • Community forum
    • Submit feedback
    • Contribute to GitLab
  • Sign in
D
Documentation
  • Project overview
    • Project overview
    • Details
    • Activity
  • Analytics
    • Analytics
    • Value Stream
  • Wiki
    • Wiki
  • Members
    • Members
  • Collapse sidebar
  • Activity
  • UB Database Group
  • Documentation
  • Wiki
  • Readinglist Graphical Visualization

Last edited by Poonam Kumari Nov 14, 2019
Page history

Readinglist Graphical Visualization

Summary

This section consists of papers on uncertainty representation and visualization using graphical methods (scatter plots, bar charts etc)

Missing Data in Interactive High-Dimensional Data Visualization

This paper describes techniques for the interactive exploratory analysis of multivariate data with missing values. A means for keeping track of the location of missing values in data is provided along with providing and accepting imputation methods. XGobi software is used for implementation.

  • Missing Data in Interactive High-Dimensional Data Visualization.pdf

Where's My Data? Evaluating Visualizations with Missing Data

In this paper authors use four categories of visualizations to present missing data in time series data. Perceived confidence, data quality and accuracy are measured. The categories used are highlighting, downplaying, annotation and visually removing information. According to the results highlighting and annotating lead to higher perceived data quality and more accurate interpretation.

  • [Where's My Data? Evaluating Visualizations with Missing Data.pdf] (/uploads/e146e0ad3b364b91169089f268b62e4e/song_VIS_2018.pdf)

Effects of visualizing missing data: an empirical evaluation

In this paper the effects of visualizing data on on decision maker’s degree of confidence and number of safer and riskier choices are measured. Emptiness, fuzziness and emptiness+explanation are used to present missing data. It is shown that Emptiness + Explanation lead to increased degree of confidence and more number of riskier choices.

  • [Effects of visualizing missing data: an empirical evaluation.pdf] (/uploads/654683b816f01476f9f75b143854b3d5/EffectsVisualizingMissingDataAnEmpiricalEvaluation-AndreassonRiveiro_slutgiltigversion.pdf)

Comparing Uncertainty Visualizations for a Dynamic Decision-Making Task

Authors compare uncertainty visualization techniques transparency and numeric annotations using a missile defense game. User has to decide whether an object is a missile or not before it reaches a town and destroy it. The results show continued support for the use of graphical uncertainty representations, even when numeric representations are present.

  • [Comparing Uncertainty Visualizations for a Dynamic Decision-Making Task.pdf] (/uploads/f1b871a6f553da73aad386906fbd4443/1555343411415793.pdf)

Uncertainty Visualizations: Helping Decision Makers Become More Aware of Uncertainty and Its Implications

Authors use three variations of a domain independent decision making system called as DSS. Participants were tested on no DSS (control), uncertainty DSS and certainty DSS. According to the results uncertainty DSS was the best. Participants seek additional information as well.

  • [Uncertainty Visualizations: Helping Decision Makers Become More Aware of Uncertainty and Its Implications.pdf] (/uploads/5e0a778b3022336f5db029137c77b87a/1555343411432338.pdf)

Visualizing Missing Data: Graph Interpretation User Study

Authors use misleading display, absent display and coded display techniques to visualize missing data. Absent display and coded display were preferred. Participants dealing with misleading display behaved as if the data was straightforward.

  • [Visualizing Missing Data: Graph Interpretation User Study.pdf] (/uploads/bc232e9fdf33b231d9a674475e50bb9a/Eaton2005_Chapter_VisualizingMissingDataGraphInt.pdf)

Visualizing Data with Bounded Uncertainty

The paper focuses on visualizing bounded uncertainty and presents a new technique called ambiguation. Ambiguation is a systematic technique based on widening the boundaries and positions of graphical elements and rendering the uncertain region in fuzzy ink

  • Visualizing Data with Bounded Uncertainty
Clone repository
  • 2016 Ketter133A
  • 2018 JITD Testbed Sketch
  • Annotation Provenance
  • Conferences
  • Datasets
  • Deploy a Service on Gram
  • FacilitiesStatement
  • GraphingTools
  • HTTPServerSourceCode
  • Hardware
  • LibraryGatewayHack
  • Machine Dumbo
  • Machine Gram
  • Machine Gungnir
  • Machine Mjolnir
View All Pages