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.
Open-source software for volunteer computing and grid computing.
☢️👁️ Hardware for a hackable DIY gamma-ray spectrometer using a popular NaI(Tl) scintillator, SiPM and a Raspberry Pi Pico.
📱🌐📋 wq: a modular framework supporting web / native apps for mobile surveys and geospatial data collection. Powered by Django REST Framework, Redux, React, and Material UI.
🔬 A repository of resources related to citizen, community-based and/or non-institutional science
Python client for iNaturalist
☁ DIY Air Quality Monitoring Device
Deep learning models and dataset for recognizing industrial smoke emissions
💻📱 wq's app library: a JavaScript framework powering offline-first web & native apps for geospatial data collection, mobile surveys, and citizen science. Powered by Redux, React, Material UI and Maplibre GL.
☁🌐 wq's db library, extending Django REST framework to support apps for geospatial field data collection, citizen science, and crowdsourcing.
KnowFlow Automatic Water Monitoring device is an open sourced tool enable everyone having access to first hand water quality data with low cost.
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
Powering openhumans.org
Open and Affordable Quantitative Imaging Platform
rete monitoraggio ambientale partecipativo documentation at https://doc.rmap.cc
A curated list of awesome resources on crowdsourcing, human computation, and online behavioral experiments.
Code respository for AutSPACEs: the Autistica/Turing citizen science platform
Spectral and radiometric calibration of consumer cameras (SPECTACLE).
A Python-Django web application enabling users to upload, share, and display data from their environmental monitoring sites via the app's ODM2 database. Data can either be automatically streamed from Internet of Things (IoT) devices, manually uploaded via CSV files, or manually entered into forms.