Discipline: Ecology Environmental and Earth Sciences
Subcategory: Geosciences and Earth Sciences
Room: Park Tower 8212
Robert Mckinzie - Bethune-Cookman University
Co-Author(s): Dr. Raphael Isokpehi, Bethune-Cookman University, Daytona Beach, Fl
With the rapid evolution of massive data collection and analysis technology, meteorologists and weather centers are constantly attempting to innovate the presentation of meteorological data for effective deliverance and communication to the public. The bright, vivid colors used in weather forecasts and Doppler radars are examples of visualizations tools. Characterization of meteorological data analysis tasks and the corresponding structure of information distribution will provide bases of understanding on development, trend, and usage of visualization tools in meteorological information dissemination. The goal of the research is to understand the functions of visualization in meteorological data analyses through textual coding, mining, and annotation. The research process involved stages of software supported tasks on textual data structures (sentences and references) from a selected seed scholarly article, ‘Visualization in Meteorology – A Survey of Techniques and Tools for Data Analysis Tasks’. The process results in datasets and interactive visualizations that support the performance of five content types including concept, fact, procedure, process, and principle. A total of 605 sentences were extracted and annotated for the presence of content knowledge in the five categories and selected key words and their derivatives such as weather, climate, meteorology, data analysis, visualization. Groups of sentences were obtained using a 10-digit binary code model, which were further analyzed using conventional statistical methods. Patterns of knowledge included sentences that describe visualization tools and techniques involved in data analyses and dissemination in meteorology. Further research could investigate the skills to increase the speed of alerts and warnings. It is imperative to have fast and accurate weather alerts to help families perform the correct precautionary action.
Funder Acknowledgement(s): This publication was made possible by the National Science Foundation Award: CSE-1829717 (CyberTraining:CIU:Computational and Data Science Literacy Curriculum Exchange) and the National Oceanic and Atmospheric Administration, Office of Education Educational Partnership Program award (NA16SEC4810009). Its contents are solely the responsibility of the award recipient and do not necessarily represent the official views of the U.S. Department of Commerce, National Oceanic and Atmospheric Administration. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Commerce, National Oceanic and Atmospheric Administration.
Faculty Advisor: Dr. Hyun Jung Cho and Dr. Raphael Isokpehi, firstname.lastname@example.org
Role: I conducted the texting mining and annotating of the scholarly article. Through textual analysis, i constructed a data-set in an Excel spreadsheet. After the completion of the data-set, I extracted the data into Tableau Software. I use Tableau software to assist with data analytics and provide visuals of the data.