Campaing data obtained from the Micro Volunteering Engine

This database supports the task allocation solution for a Spatial Crowdsourcing problem within the context of the Socio-Bee project. The goal is to resolve the task allocation challenge in a scenario where participation is altruistic, without economic incentives. Instead, recommendations are tailored to users based on their routines and past involvement, encouraging ease of participation by making tasks adaptive to their availability and location.

The database is designed as part of the second pilot of the Socio-Bee project, a Citizen Science initiative aimed at promoting public involvement in air quality monitoring. In this project, users (citizen scientists) perform air quality measurements to create a spatially distributed data map, enhancing our understanding of environmental conditions across specific areas.

For further details on the algorithmic design and implementation of the recommendation system, please refer to the project repository at GitHub - RecommenderSystem.