Faculty Advisor/Mentor
Holly A. H. Handley
Location
Virginia Modeling, Analysis and Simulation Center, Room 1201
Conference Title
Modeling, Simulation and Visualization Student Capstone Conference 2023
Conference Track
Data Science
Document Type
Paper
Abstract
Although visualization is beneficial for evaluating and communicating data, the efficiency of various visualization approaches for different data types is not always evident. This research aims to address this issue by investigating the usefulness of several visualization techniques for various data kinds, including continuous, categorical, and time-series data. The qualitative appraisal of each technique's strengths, weaknesses, and interpretation of the dataset is investigated. The research questions include: which visualization approaches perform best for different data types, and what factors impact their usefulness? The absence of clear directions for both researchers and practitioners on how to identify the most effective visualization approach for a specific data type poses a significant research challenge. Our findings will help both professionals and researchers determine the most successful visualization approach for different data types, as well as identify topics for future study in the field of data visualization.
Keywords:
Data analysis, Decision-making, Information visualization, Visualization techniques, Data communication, Data interpretation
Start Date
4-20-2023
End Date
4-20-2023
Recommended Citation
Yalim, Cansu and Handley, Holly A. H., "The Effectiveness of Visualization Techniques for Supporting Decision-Making" (2023). Modeling, Simulation and Visualization Student Capstone Conference. 1.
https://digitalcommons.odu.edu/msvcapstone/2023/datascience/1
DOI
10.25776/y65q-qy42
Included in
Categorical Data Analysis Commons, Computational Engineering Commons, Data Science Commons, Longitudinal Data Analysis and Time Series Commons
The Effectiveness of Visualization Techniques for Supporting Decision-Making
Virginia Modeling, Analysis and Simulation Center, Room 1201
Although visualization is beneficial for evaluating and communicating data, the efficiency of various visualization approaches for different data types is not always evident. This research aims to address this issue by investigating the usefulness of several visualization techniques for various data kinds, including continuous, categorical, and time-series data. The qualitative appraisal of each technique's strengths, weaknesses, and interpretation of the dataset is investigated. The research questions include: which visualization approaches perform best for different data types, and what factors impact their usefulness? The absence of clear directions for both researchers and practitioners on how to identify the most effective visualization approach for a specific data type poses a significant research challenge. Our findings will help both professionals and researchers determine the most successful visualization approach for different data types, as well as identify topics for future study in the field of data visualization.