Citizen science is a form of scientific research in which members of the public participate. It is often used to describe scientific research conducted by amateur scientists, but it can also be used to describe scientific research conducted by professional scientists that involve members of the public.
Python client for iNaturalist
Deep learning models and dataset for recognizing industrial smoke emissions
☁🌐 wq's db library, extending Django REST framework to support apps for geospatial field data collection, citizen science, and crowdsourcing.
Open and Affordable Quantitative Imaging Platform
Powering openhumans.org
An Observatory Control System for the PANOPTES citizen-science project designed to help find transiting exoplanets! 🔭 🌠
Web API to easily access satellite-based emission data
Code respository for AutSPACEs: the Autistica/Turing citizen science platform
Spectral and radiometric calibration of consumer cameras (SPECTACLE).
The web application for Monitor My Watershed, enabling users to upload, share, and display environmental Internet of Things (IoT) and other monitoring data to the Internet of Water (IoW). Built on the ODM2 data system.
Celestial navigation toolkit. Can be used in a mobile phone or tablet (Celeste app for Android) without internet connection.
An application to automatically recognize birds, specify the species, count and save pictures of them, only by use of one camera and a Raspberry Pi. The images and recorded values are made available online on https://opensensemap.org/.
📑⚙️ Python/Django reference implementation of the ERAV data model
A curated list of awesome Citizen Science Projects in the Netherlands
FITS to Azimuth/Elevation using Astrometry.net--calibrate and plate scale images
The Django app behind Mosquito Alert platform.
Package to input data from sensors / ROS-enabled telemetry agent
Notebooks to upload/download marine footage, connect to a citizen science project, train machine learning models and publish marine biological observations.
Live crowdsourced research platform measuring how well humans detect AI-generated news - dual-axis authenticity judgments, gamified challenge mode & shareable score cards. The human-perception half of the RogueGPT pipeline.