Representing Data Quality for Streaming and Static Data

In smart item environments, multitude of sensors are applied to capture data about product conditions and usage to guide business decisions as well as production automation processes. A big issue in this application area is posed by the restricted quality of sensor data due to limited sensor precision as well as sensor failures and malfunctions. Decisions derived on incorrect or misleading sensor data are likely to be faulty. The issue of how to efficiently provide applications with information about data quality (DQ) is still an open research problem. In this paper, we present a flexible model for the efficient transfer and management of data quality for streaming as well as static data. We propose a data stream metamodel to allow for the propagation of data quality from the sensors up to the respective business application without a significant overhead of data. Furthermore, we present the extension of the traditional RDBMS metamodel to permit the persistent storage of data quality ...

• Type: Conference
• Year: 2007
• Where: ICDE
• Authors: Anja Klein, Hong Hai Do, Gregor Hackenbroich, Marcel Karnstedt, Wolfgang Lehner
• Keywords: Data Quality, Database, ICDE 2007, Sensor Data, Sensors