QuoVidi

QuoVidi organizes geotagged photographic quests to teach botanical and zoological systematics and taxonomy and to generate annotated biodiversity image datasets for research and education.

Key Features:

• Quest-based assignments: Quests comprise morphologic, ecological, or systematic terms that participants must locate and document in the environment.
• Geotagged photographic evidence: Participants capture and upload geotagged photographs as evidentiary records tied to specific quests.
• Educator validation and annotation: Submissions are evaluated and validated by educators for taxonomic or descriptive accuracy.
• Image database generation: Validated submissions accumulate into large image databases analogous to citizen-science projects.
• Team-based fieldwork organization: The platform organizes participants into teams to perform coordinated quests and submissions.
• Implementation stack: The application is implemented in R using the Shiny package.
• Customizable quest content: Quest definitions can be modified to target different taxonomic groups or other disciplines.

Scientific Applications:

• Systematics and taxonomy education: Supports teaching and assessment of specialized botanical and zoological vocabulary and identification skills.
• Biodiversity data collection: Produces large-scale photographic datasets suitable for biodiversity monitoring and research akin to citizen-science repositories.
• Remote assessment of observations: Enables educators to monitor and assess large cohorts of student field observations remotely via validated submissions.
• Support for restricted-access contexts: Facilitates participation from low-biodiversity or restricted-access settings by allowing submission and evaluation of previously validated images.

Methodology:

Participants capture geotagged photographs and upload them to the platform; educators evaluate and validate submissions, which are stored in an image database; the application is implemented in R using the Shiny package.