Interactive evolution, where users' preferences guide the search, is one of the techniques employed by Evolutionary Art researchers. It can be implemented as a web application to lower the access threshold since it often depends on volunteers who visit the system for fitness assignment. However, several drawbacks limit user participation: human fatigue and boredom result from evaluating a large number of phenotypes. To tackle these issues, in this paper we propose an IEC system designed using a human-centered approach, with a framework consisting of a social network of volunteers interacting with a population also consisting of a network of phenotypes. The use of a graph model is proposed as a practical and efficient tool for mapping the relationships between actors and objects in the system. A case study is presented as proof-of-concept, providing both conceptual and implementation details of the graph model as it is applied in the implementation of an IEC system. Our experiments show that the data model can be successfully used to implement a gamification technique developed to increase users' engagement, which implies that this technique can be successfully used to decrease user fatigue and thus increase the performance of the interactive system. experiments show that the data model can be successfully applied in a gamification technique developed to increase user engagement, which implies that this technique can successfully be used to decrease user fatigue and thus increase performance of the interactive system.
