Internet of Things (IoT) has become the essential technology, which supports the safety, innovation and sustainable development of cold chain monitoring services. Since the complex technical structure and diverse data formats, there are still many challenges in current application scenarios in the cold chain monitoring services based Internet of things. From the perspective of data, the data quality problem in the monitoring process in cold chain was comprehensively analyzed and examined, in order to enhance the data awareness in the cold chain monitoring applications and its services. And thus inspire the relevant scholars to solve the data quality and optimization issues in clod chain monitoring based IoT. In light of the data quality generation mechanism, data quality assessment methods and application improvement practices, the current research status and the development trends were summarized in line with the life cycle of monitoring data in cold chain. The research and analysis indicated that the measurement and evaluation of data quality became the key to the ongoing improvement of the data quality in IoT in cold chain, which emphasized that the data quality should be handled in the process of where the data generation from the perspective of data quality. It also pointed out that the combination of assessment methods, application scenarios, and requirements differentiation was increasingly tight. And the future research should enhance the process of data retrieval through integrating data characteristics of monitoring technologies and the generation process in cold chain, and cold chain monitoring data quality should enhance the collaboration and mining of monitoring technical characteristics and their performances.