The Mars crowdsourcing experiment is crowdsourcing in the fom of a serious game applicable for annotation in a semantically-rich research domain?

This study investigates crowdsourcing using a serious game concerning the annotation of semantically rich features of Mars. Photographic data is used transmitted from the Mars Reconnaissance Orbiter recording the surface. A computer game, called Cerberus, was developed allowing players to tag features of the Mars surface. The game investigated in four different conditions what the effects were of different help levels to support knowledge transfer and different levels of game features to provide the players with a stimulating game experience. The performance of the participating players was measured in terms of precision and motivation. Precision reflects the quality of the work done and motivation is represented by the amount of work done by the players. The four game conditions varied in an implicit and an explicit level of help and poor and rich game features. The game condition with the explicit help function combined with the rich game experience showed significantly more motivation among the players than the game condition with the implicit help function combined with the poor gaming experience. Precision did not show any significant difference between the game conditions, but was high enough to generate Mars maps exposing aeolian processes, surface layering, river meanders and other concepts. Apparently the players were capable of acquiring deeper concepts about Mars's geology and the results were of such a high quality that they could be used as input for and to reinforce scientific research.