Identifying stops and trips from raw GPS traces is a fundamental preprocessing step for most mobility research applications. Thus, ensuring the excellent accuracy of such systems is of high interest to researchers designing such analysis pipelines. While there are plenty of GPS datasets available, these usually do not provide annotations and thus cannot be used for benchmarking stop/trip classifiers easily. This dataset contains GPS & accelerometer records, including accurate stop/trip annotations. It includes 122,808 GPS samples as one continuous trajectory, spanning over 126 days (78,900 labeled stops and 43,908 labeled trips). The recorded time frame includes working days, vacations, traveling, everyday life, and all regular modes of transportation. During recording, a detailed mobility diary was conducted to capture each dwelling period's exact beginning and end. This dataset belongs to the manuscript titled "The STAGA-Dataset: Stop and Trip Annotated GPS and Accelerometer Data of Everyday Life," presented at the FOSS4G conference in August 2022, Florence, Italy.