Abstract—The rapid growth of the Industrial Internet ofThings (IIoT) has led to the generation of vast amounts ofdata, which has significant implications for decision-making invarious industrial sectors and is increasingly being traded on datamarketplaces. Quantifying IIoT data quality and providing measuresto improve, it is critical for both operational efficiency andbusiness value. This paper presents a comprehensive architecturefor data quality assessment in the IIoT, aimed at ensuring thequality, trustworthiness, and reliability of the data generated bythe IIoT. The architecture facilitates both objective and subjectiveassessments, taking into account the intended task for the data,and includes data enhancement operations to address data qualityissues. The architecture provides a standardized and modularapproach to data quality evaluation, allowing data owners anddata market participants to make informed decisions about thequality and value of their data. The proposed architecture hasthe potential to significantly impact various industrial sectorsand data marketplaces, providing a valuable tool for ensuringthe reliability and accuracy of IIoT data. As the architecture is awork in progress, the preliminary evaluation of its effectivenesshas been omitted for future work.