Existing studies in mobile crowdsourcing (aka spatial crowdsourcing), a hot research area in recent years, face the problem of lacking realworld datasets. We thus published a synthetic dataset generator for producing common datasets for mobile crowdsourcing.
The toolbox can generate synthetic workload patterns based on the spatial (location) and temporal (time) distributions of workers and tasks. As shown in the figure below, it also takes into account the various real-world constraints, such as worker region and worker capacity, worker activeness and temporal workload.
Link to the toolbox
Hien To, Mohammad Asghari, Dingxiong Deng, and Cyrus Shahabi, SCAWG: A Toolbox for Generating Synthetic Workload for Spatial Crowdsourcing, In Proceeding of International Workshop on Benchmarks for Ubiquitous Crowdsourcing: Metrics, Methodologies, and Datasets (CROWDBENCH 2016), Sydney, Australia, March 14-18, 2016