Data quality management is the mature processes, tools, and in-depth understanding of data you need to make decisions or solve problems to minimize risk and impact to your organization or customers. Data quality management in IoT is the practice of using that IoT data to serve your purposes with flexibility and agility for IoT applications. To do this, it is necessary to assess what data you have today and the processes and tools that use or support data against purposes and requirement of IoT applications. The requirements for data and its quality vary from IoT application to application or organization in different contexts. Data quality management practice in IoT makes data a holistic asset, by which it means that data is the input and output of every task and transaction performed according to IoT application for a business. This Recommendation specifies key requirements with respect to data quality management in IoT and important elements to fulfil these requirements. This document indicates the requirements and functional model in terms of the scopes of the followings: data quality management in IoT, requirements of data quality management in IoT and Functional model to support data quality management.