Prof. Stephen Serjeant and Dr. Hugh Dickinson
The ESCAPE Citizen Science (CS) brings the science-inclined public directly and genuinely into the processes of scientific discovery, through a harmonised suite of citizen science experiments, improving the transparency of the scientific process. The ESCAPE CS also gives the public the opportunity to have a direct two-way dialogue with the professional science teams and a tangible connection with the ESFRI projects facilitated by the EOSC framework. In parallel we will also develop machine learning tools, trained initially on crowdsourced data, to accelerate volunteer classifications during the operation of the citizen science projects.
Besides the experiments with embedded educational resources, the ESCAPE CS will provide a public engagement video series, highlighting the data-science for the ESFRI facilities opened up by the implementation of EOSC and inviting the viewers to participate in a related mass participation experiment.
The science-inclined public and the expert specialist science communities
If you're interested in astronomy or physics, and you want to make a real scientific contribution, come join our citizen science projects and be part of the open science revolution!
We provide the science-inclined public with the most accessible way to get genuinely involved in the scientific discoveries of the astronomy and physics ESFRI facilities in the EOSC. The benefits to the scientific communities are that volunteer crowdsourcing is the best approach for many complex scientific data mining problems, and it has an excellent track record for finding unexpected features missed by automated data processing.
Ours is the best approach for getting the general public genuinely involved in the scientific discoveries of the astronomy and physics facilities in the European open science cloud. The citizen science methodology is uniquely well suited to many data mining challenges faced by the ESFRIs in the EOSC.