Data collection is an important aspect of all research, be it in the fields of sciences, humanities or business. Participatory data collection, in particular, poses a challenge to all fields of study as the required data for modern research often exceeds the amount that is provided by voluntary participants. It is therefore essential to find more people who are willing to submit their data. This thesis suggests and investigates potential designs for mobile applications that motivate volunteers and provide incentives for participation. First, multiple design methods are introduced and explained ranging from reward-based designs, over gamification and storytelling, to the integration of social networks. Five designs incorporating these methods are then suggested and evaluated via an online survey. The designs focus on a mobile application that uses symptom questionnaires to predict the spreading of influenza-like diseases. Utilizing the results of the survey, a prototype using the design with the highest potential is implemented on Android to further assess its effectiveness. The prototype is evaluated in a user study using ContraVision – interviews about two videos showing the positive and negative aspects of the design. Results of this work provide potential design methods that increase motivation to participate in data collection. The acquisition of more data allows for more research questions to be answered and ensures correct assumptions for further research.