EasyTrack - Orchestrating large-scale mobile user experimental studies

Abstract

In recent years, large-scale data collection has become crucial in Human-Computer Interaction (HCI) research. With a sharp climb of the amount of data being gathered due to an increasing number of mobile and wearable devices, real-time maintenance of Data Quality (DQ) of data-collection campaigns has already become an overwhelming task, especially in large-scale experiments. This paper proposes EasyTrack, a platform that collects large-scale data in an automatized manner. We describe how our proposed solution detects and tackles issues in data collection campaigns in an automated manner.