BiodiversityOS is built on open-source web technologies with a focus on accessibility, data integrity, and transparency. This article describes the platform's technical approach and the principles behind it.
Web Architecture
The platform is built with Next.js, a React-based framework that enables server-side rendering and static generation. This ensures that species profiles, the map interface, and content pages are fast-loading and accessible to search engines without requiring JavaScript execution.
Interactive mapping uses Leaflet, an open-source mapping library, with CartoDB basemap tiles. The map component supports filtering by species, date range, and behavior — allowing researchers to explore observations spatially.
Open Data Principles
BiodiversityOS is designed around the principle that biodiversity data is a public resource. Observations are intended to be openly accessible rather than locked behind institutional subscriptions or proprietary databases.
This draws on the growing DeSci (Decentralized Science) movement, which advocates for scientific outputs that are transparent, community-governed, and not dependent on any single institutional infrastructure. For biodiversity data, this means prioritizing long-term accessibility over convenience of centralized control.
Data Quality Through Structure
Citizen science data quality depends on how observations are collected. BiodiversityOS uses structured submission forms to standardize what is recorded with each sighting: species, date, GPS coordinates, depth, observed behavior, and photographic evidence when available.
Community verification adds a quality layer. Submissions are reviewed by contributors with local ecological knowledge — the same kind of knowledge that Mar Sustentable has incorporated into its field research since 2015.
Attribution
Contributors receive attribution for their observations. This is designed into the data model, not added as an afterthought. Proper attribution matters both for recognizing individual contributors and for making the provenance of each data record clear to researchers who use it.
For the local communities — fishers, divers, guides — whose ecological knowledge has historically been used without formal credit, attribution is a matter of scientific integrity as much as recognition.