Internet of Things (IoT) systems manage an overwhelming quantity of data created by a huge number of sensors spread out across an expansive geographical region. The goal of the gathered data is to be assembled to provide clear information to generate useful knowledge. Making good decisions depends on sufficient and accessible information. Thus improving Information Quality (IQ) yields a better value from the system. There is, however, no common consensus on how to manage IoT IQ within a whole quality structure. Despite numerous studies on managing IQ, there appears to be a lack of comprehensive strategies to aid managers in developing the quality of information for IoT devices. As a result, a comprehensive framework is required to map the understanding of information quality for IoT systems in order to plan quality improvements. Because information is a product for the IoT, this thesis treats data quality dimensions as product components and IoT elements as product technical requirements. In this thesis, design science is used as a research methodology to create a novel information quality framework that IoT developers and quality managers can adapt as a guideline to manage IoT system quality. The thesis research methodology consists of problem investigation, treatment design, and treatment validation. The problem investigation includes a comprehensive literature review of information quality for IoT systems. The treatment design is based on studying literature gaps and analyzing the framework perspectives and TQM techniques. For validation, the research uses the comparison method, experts' opinions, and a single-case study. The medical wearables single-case study is selected for demonstration and validation. This validation methodology is suitable considering the nature of the research outcomes. The thesis outcome can be explained as a comprehensive framework to map the current IQ for IoT systems by integrating the House of Quality (HoQ) technique. The developed framework is a dynamic management guideline