Developing An Extendable Web-Based Architecture For Honey Bee Data Visualization
- ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
- Gurney Buchanan (Creator)
- Institution
- Appalachian State University (ASU )
- Web Site: https://library.appstate.edu/
- Advisor
- Rahman Tashakkori
Abstract: Over the past 10 years, a paradigm shift has occurred in the field of web development as websites became web applications. Although hard to define, web applications usually refer to sites with a focus on providing responsive experiences that incorporate complex and dynamic functionality. This shift in complexity is accompanied by a shift in web technologies, as traditional LAMP stack (Linux, Apache, MySQL, and PHP) websites are replaced by JavaScript-based web applications built upon new technologies such as the MEAN stack (MongoDB, ExpressJS, Angular, and Node.js). As these new technologies become widely accepted, the need for a general and adaptable architecture for web-based dynamic data visualization using JavaScript has grown. This thesis details such an architecture. Our architecture seeks to be extendable, flexible, and largely platform agnostic, however, it is specifically designed to leverage new web paradigms such as WebSockets and full stack JavaScript web application frameworks. As a proof of concept, we have applied this architecture in a web application for the visualization of automatically analyzed honey bee hive data from the BeeMon project. This web application presents our framework in a practical scenario and provides a basic implementation for others to extend and adapt to their specific needs.
Developing An Extendable Web-Based Architecture For Honey Bee Data Visualization
PDF (Portable Document Format)
878 KB
Created on 5/28/2019
Views: 850
Additional Information
- Publication
- Thesis
- Buchanan, G. (2019). Developing An Extendable Web-Based Architecture For Honey Bee Data Visualization. Unpublished Master’s Thesis. Appalachian State University, Boone, NC.
- Language: English
- Date: 2019
- Keywords
- Full Stack Web Development, MEAN Web Stack, Software Engineering, Data Visualization, Software Architecture