SharkPulse App

Hagood, Mia; Warner, Patrick; Tran, Anhtuan Vuong

SharkPulse App

dc.contributor.author	Hagood, Mia	en
dc.contributor.author	Warner, Patrick	en
dc.contributor.author	Tran, Anhtuan Vuong	en
dc.date.accessioned	2024-05-10T02:25:09Z	en
dc.date.available	2024-05-10T02:25:09Z	en
dc.date.issued	2024-05-09	en
dc.description	SharkPulsePresentation.pdf PDF of our final presentation SharkPulsePresentation.pptx Powerpoint of our final presentation SharkPulseReport.pdf PDF of our final report ShrakPulseReport.docx Word Document of our final report SharkPulseScripts.zip - Finalized scripts for dynamic visualizations	en
dc.description.abstract	This project is an extension of work that has been done in previous years on the sharkPulse website. sharkPulse was created due to the escalating exploitation of shark species and the difficulty of classifying shark sightings. Due to sharks’ low population dynamics, exploitation has only exacerbated the issue and made sharks the most endangered group of marine animals. sharkPulse retrieves sightings from several sources such as Flickr, Instagram, and user submissions to generate shark population data. The website utilizes WordPress , HTML, and CSS for the front end and R-Shiny, PostgreSQL, and PHP to connect the website to the back end database. The team was tasked with improving the general usability of the site by integrating dynamic data-informed visualizations. The major clients of the project are Assistant Professor Franceso Ferreti from the Virginia Tech Department of Fish and Wildlife Conservation and Graduate Research Assistant Jeremy Jenrette. The team established regular contact through Slack, scheduled weekly meetings online with both clients, and acquired access to all major code repositories and relevant databases. The team was tasked with creating dynamic and data-informed visualizations, general UI/UX improvements, and stretch goals for improving miscellaneous pages throughout the site. The team developed PHP scripts to model a variety of statistics by dynamically querying the database. These scripts were then sourced directly through the site via the Elementor WordPress module. All original requirements from the clients have been met as well as some stretch goals established later in the semester. The team created a Leaflet global network map of affiliate links which dynamically sourced the sharkPulse social network groups from an Excel spreadsheet and generated country border markers and links to each country’s social network sites as well as a Taxonomic Accuracy Table for the Shark Detector AI. The team created and distributed a survey form to collect user feedback on the general usability of the site which was compiled and sent to the client for future work.	en
dc.identifier.uri	https://hdl.handle.net/10919/118941	en
dc.language.iso	en	en
dc.rights	Creative Commons Attribution 4.0 International	en
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	en
dc.subject	Sharks	en
dc.subject	Web Application	en
dc.subject	Conservation	en
dc.subject	SharkPulse	en
dc.subject	Classification	en
dc.subject	Data Visualization	en
dc.subject	User Experience	en
dc.title	SharkPulse App	en
dc.type	Report	en
dc.type	Presentation	en
dc.type	Software	en