Extending Data Quality Management for Smart Connected Product Operations

Abstract

Smart connected product (SCP) operation embodies the concept of the internet of things (IoT). To increase the probability of success of SCP operations for customers, the high quality of the IoT data across operations is imperative. IoT data go beyond sensor data, as integrate some other various type of data such as timestamps, device metadata, business data, and external data through SCP operation processes. Therefore, traditional data-centric approaches that analyze sensor data and correct their errors are not enough to preserve, in long-term basis, adequate levels of quality of IoT data. This research provides and alternative framework of data quality management as a process-centric approach to improve the quality of IoT data. The proposed framework extends the process reference model (PRM) for data quality management (DQM) defined in ISO 8000-61, and tailored to fully adapt to the special requirements of the IoT data management. These involve several adaptations: first, the scope of the SCP operations for data quality management is determined, and the processes required for SCP operations are defined following the process description format of ISO 8000-61. Second, the relationship between the processes and the structure of the processes in the technology stack of the SCP operations are described to cover the actual nature of the IoT data flows. Finally, a new IoT DQM-PRM is proposed by integrating the processes for the SCP operations with DQM-PRM. When these processes are executed in the organization, the quality of IoT data composed of data of various types can be continuously improved and the utilization rate of SCP operations is expected to increase.