Modern industrial production and quality systems rely on a variety of sensors and sensor systems to qualify the conformity of a product to given specifications and requirements. Sensors are used in metrology and testing in numerous applications. They are used to capture qualified data, automate and control processes, and to secure product quality. Sensors are the key elements to generate real-world data and to feed trustworthy data into digital models or digital twins. In a truly digital quality infrastructure, consistency of data from metrology and testing is essential. It is a complex and challenging task to digitalize the quality infrastructure, to cover the whole range from manual or semiautomated settings for testing to numerous sensors distributed in modern Internet of Things (IOT)-based factory environments. A stringent chain of traceable digital information from testing, metrology, and calibration is desired in order to provide measurement and calibration data in a machine readable and machine interpretable way for a trusted digital quality infrastructure. Furthermore, quality indicators (QoX) can be used to convey supplementary information on the trustworthiness of the respective data reported. The Industry 4.0 scenario uses the asset administration shell (AAS) and digital product passport (DPP) to document and report quality-related data and documents for a given product or sensor. A respective AAS sub-model for digital quality documents is under development at the Industrial Digital Twin Association (IDTA) to serve as a common data structure for a variety of quality documents from testing, metrology, calibration, and conformity assessment.