Data quality management (DQM) is one of the most critical aspects to ensure successful applications of the Internet of Things (IoT). So far, most of the approaches for assuring data quality are typically data-centric, i.e., mainly focus on fixing data issues for specific values. However, organizations can also benefit from improving their capabilities of their DQM processes by developing organizational best DQM practices. In this regard, our investigation addresses how well organizations perform their DQM processes in the IoT domain. The main contribution of this study is to establish a framework for IoT DQM maturity. This framework is compliant with ISO 8000-61 (DQM: process reference model) and ISO 8000-62 (DQM: organizational process maturity assessment) and can be used to assess and improve the capabilities of the DQM processes for IoT data. The framework is composed of two elements. First, a process reference model (PRM) for IoT DQM is proposed by extending the PRM for DQM defined in ISO 8000-61, tailoring some existing processes and adding new ones. Second, a maturity model suitable for IoT data is proposed based on the PRM for IoT DQM. The maturity model, named IoT DQM3, is proposed by extending the maturity model defined in ISO 8000-62. However, in order to increase the usability of IoT DQM3, we consider adequate the proposition of a simplification of the IoT DQM3, by introducing a lightweight version to reduce assessment indicators and facilitate its industrial adoption. A simplified method to measure the capability of a process is also suggested considering the relationship of process attributes with the measurement stack defined in ISO 8000-63. The empirical validation of the maturity model is twofold. First, the appropriateness of the two models is surveyed with data quality experts who are currently working in various organizations around the world. Second, in order to demonstrate the feasibility of the proposal, the light-weight version is applied to a manufacturing company as a case study.

数据质量管理 (DQM) 是确保物联网 (IoT) 成功应用的最关键方面之一。到目前为止，大多数确保数据质量的方法通常是以数据为中心的，即主要侧重于解决特定值的数据问题。但是，组织也可以通过开发组织最佳 DQM 实践来提高其 DQM 流程的能力。在这方面，我们的调查解决了组织在物联网领域执行其 DQM 流程的情况。本研究的主要贡献是建立物联网 DQM 成熟度框架。该框架符合 ISO 8000-61（DQM：流程参考模型）和 ISO 8000-62（DQM：组织流程成熟度评估），可用于评估和改进物联网数据的 DQM 流程的能力。该框架由两个元素组成。首先，通过扩展 ISO 8000-61 中定义的 DQM 的 PRM，裁剪一些现有流程并添加新流程，提出了 IoT DQM 的流程参考模型 (PRM)。其次，基于物联网 DQM 的 PRM 提出了适用于物联网数据的成熟度模型。成熟度模型名为 IoT DQM3，是通过扩展 ISO 8000-62 中定义的成熟度模型而提出的。然而，为了提高 IoT DQM3 的可用性，我们充分考虑了简化 IoT DQM3 的提议，通过引入轻量级版本来减少评估指标并促进其工业采用。考虑到过程属性与 ISO 8000-63 中定义的测量堆栈之间的关系，还建议了一种测量过程能力的简化方法。成熟度模型的实证验证是双重的。首先，目前在世界各地的各种组织中工作的数据质量专家对这两种模型的适用性进行了调查。其次，为了论证该方案的可行性，将轻量版应用到一家制造企业作为案例研究。