Development of a Data Sonification Tool to Transcend Standard Visualization Analyses
Jacob Elbirt, Ali Qusay Al-Faris · 2023
Data manipulation and analysis are critical for companies, researchers, and universities to identify trends and aggregate additional information from existing numerical data. Data normalization and logarithmic transformations are standard alterations used to improve data readability in graphs, charts, and other representations. Spreadsheet applications like Microsoft Excel, Google Sheets, and Apple Numbers provide tools for addressing these tasks but quickly become cumbersome and time- consuming, requiring considerable understanding and experience with spreadsheet applications, data formatting and chart generation. While visual representations with their complications are common in spreadsheet applications, audio analysis and representation are largely untapped resources in this capacity. This work presents an approach to sonifying numerical datasets received in spreadsheet format and transforms the data into audio representation that plays during chart generation. The approach involves developing software in the Java programming language. This software is also important in providing a unique opportunity to express datasets and trends to individuals who are blind or otherwise visually impaired.