The Citizen Science Project Builder is a web-based tool that allows volunteers to participate in complex data classification tasks that automatic tools cannot handle. It supports projects where citizens can analyze or enrich existing data, typically large sets of images or texts, such as satellite pictures or social media posts, as well as other media formats such as videos and scanned documents. 

Citizen Science Project Builder also enables the development of CS projects that involve data classification, using a project-building interface that does not require any coding skills. The web interface is based on Crowdcrafting, a project launched in 2011 by Citizen Cyberlab, which with its underlying PyBossa open source software framework was spun out as part of the European SME SciFabric in 2015. The software is publicly available under ‘Citizen Science Center Zurich’ on Github.

Co-creation of a citizen science (CS) project requires citizens and scientists to self-organize, propose and discuss ideas, schedule meetings, conduct surveys, and much more. Decidim4CS is a digital platform for participatory citizen science and constitutes the deliberation technology used in the Crowd4SDG project. It allows citizen scientists to take an active role in CS project design and execution by making proposals, participating in ongoing debates or starting new ones, attending online meetings, making collective and democratic decisions through voting, and monitoring the implementations of these decisions.

Decidim4CS is based on decidim (‘we decide’ in Catalan), a free open-source software originally created by the Barcelona City Hall as a participatory democracy platform for cities and organizations. The source code of Decidim4CS is publicly available under the ‘Crowd4SDG’ organization on GitHub.

Getting first-hand information about an emergency situation while it is happening is important, but is often difficult to obtain in a timely fashion. The image-based social sensing tool VisualCit allows extraction of visual evidence about a situation from Twitter by searching for images posted and geolocating them. Using AI methods, VisualCit enables the user to crawl Twitter with user-defined keywords to search for posts with images.

VisualCit can apply selected filters (e.g. contains photo, occurs outdoors etc.). It can associate locations to posts, even if tweets are not natively geolocated. Posts can be evaluated by crowdsourcing initiatives using the PyBossa platform (same technology as Citizen Science Project Builder above). A collection of images for a location or thematic maps can be created to support interested users.