Context and Aim of the Workshop: This workshop was organised by the JRC work packages DigiTranScope, CSData and HUMAINT, in collaboration with the COST Action Citizen Science to promote creativity, scientific literacy, and innovation throughout Europe. The workshop was the first event within this COST Action devoted to the interaction between machine learning and action learning in citizen science, and aimed to raise awareness about opportunities and issues emerging from this interrelation.
Our deliverables in WG4 – ‘Deliverable 1: Review on participants’ requirements for volunteering in CS projects (Task 1)’ and ‘Recommendations for CS project designs that address volunteer needs (Task 1)’ both with an emphasis on technologies.
As most applications currently are isolated it would be beneficial to the entire community if modular and reusable components could be created which could be used by app developers; more or less similar to a lego-like house of apps.
The overall aim of this STSM project was to create clear and publicly understandable protocols that will familiarize with the objectives of the project, its importance and enable volunteers and other public to recognize symptoms of Phytophthora diseases.
The study under the applied STSM would use a Citizen Science platform to advance the spatial prediction of invasive forest Phytophthoras by providing the public with inexpensive location-based, time series data of unprecedented quantity and distribution.
As part of his STSM at Technion - Israel Institute of Technology under the supervision of Dr. Assaf Shwartz and Dr. Liat Levontin, Martin Jeanmougin developed a database on published studies of the motivations of citizens to participate in citizen science projects.