A Tool for Visualizing Categorical Time-series Data
Location
Room 232, Schewel Hall
Access Type
Open Access
Entry Number
91
Start Date
4-5-2023 2:00 PM
End Date
4-5-2023 2:15 PM
College
Lynchburg College of Arts and Sciences
Department
Computer Science
Keywords
Categorical Data, Visualization
Abstract
Data mining is a technique that has been used with increasing frequency to analyze large datasets. One common class of data, known as categorical time series data, is comprised of a sequence of occurrences of a predetermined set of categories. For example, genetic sequences are typically expressed using a sequence of the letters A, G, C, and T. These sequences can be extremely long. Similarly, the characters in a collection of documents could also be analyzed as categorical time series, where each character is considered a category, and each occurrence of the a letter determines a member of the categorical sequence. One method that has proved useful in the analysis of categorical time series data is scientific visualization. We have created a new tool that supports the visualization of categorical time series data using some established visualizations and some innovative visualizations. The tool uses a new Application Program Interface (API) that provides portability across a large number of devices and operating systems including Microsoft Windows, macOS, Apple iOS, Linux, and Android platforms.
Faculty Mentor(s)
Dr. Randy Ribler
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A Tool for Visualizing Categorical Time-series Data
Room 232, Schewel Hall
Data mining is a technique that has been used with increasing frequency to analyze large datasets. One common class of data, known as categorical time series data, is comprised of a sequence of occurrences of a predetermined set of categories. For example, genetic sequences are typically expressed using a sequence of the letters A, G, C, and T. These sequences can be extremely long. Similarly, the characters in a collection of documents could also be analyzed as categorical time series, where each character is considered a category, and each occurrence of the a letter determines a member of the categorical sequence. One method that has proved useful in the analysis of categorical time series data is scientific visualization. We have created a new tool that supports the visualization of categorical time series data using some established visualizations and some innovative visualizations. The tool uses a new Application Program Interface (API) that provides portability across a large number of devices and operating systems including Microsoft Windows, macOS, Apple iOS, Linux, and Android platforms.