CyLog/Game aspect: An approach to separation of concerns in crowdsourced data management

In data-centric crowdsourcing, the output data are sensitive to the incentive structure connected to the workers׳ behavior. This paper proposes to use a declarative language to explicitly handle both data computation and the incentive structure. The language models computation as a set of Datalog-like rules, and the incentive structures for the crowd as games in which players׳ (workers׳) actions affect their received payoff. The language is unique in that it introduces the game aspect that separates the code for the incentive structure from the other logic encoded in the program. This paper shows that the game aspect not only enables easier analysis and maintenance of the incentive structures but also provides a principled model of the fusion of human and machine computations. In addition, we formally discuss how the rule-based language using the game concept integrates human and machine computations, and discuss its limitation and expressive power.