Semantic Description of Quality of Data in Sensor Networks

Abstract

The annotation of sensor data with semantic metadata is essential to the goals of automation and interoperability in the context of Industry 4.0. In this contribution, we outline a semantic description of quality of data in sensor networks in terms of indicators, metrics and interpretations. The concepts thus defined are consolidated into an ontology that describes quality of data metainformation in heterogeneous sensor networks and methods for the determination of corresponding quality of data dimensions are outlined. By incorporating support for sensor calibration models and measurement uncertainty via a previously derived ontology, a conformity with metrological requirements for sensor data is ensured. A quality description for a calibrated sensor generated using the resulting ontology is presented in the JSON-LD format using the battery level and calibration data as quality indicators. Finally, the general applicability of the model is demonstrated using a series of competency questions.

Fundamental aspects in sensor network metrology

“…For instance, a machinereadable digital calibration certificate [11] could be provided by the sensor itself, e.g., using OPC-UA, or from another source, e.g., an internal quality management platform. If needed, this information could be further extended by other data which could affect the quality of measurement data [12].…”

“…In this way, one can build upon existing work and established principles and software tools. In the GEMIMEG-II project this development was extend to the integration of semantically described quality of data aspects [12].…”

“…Another common issue is drift, where sensor readings slowly deviate from the true value due to the degradation of the electronics [14]. One outcome from the GEMIMEG-II project is a framework for quality of data in sensor networks, expressed in terms of an ontology [12]. This can be expressed, for instance in an ontology [12].…”

“…One outcome from the GEMIMEG-II project is a framework for quality of data in sensor networks, expressed in terms of an ontology [12]. This can be expressed, for instance in an ontology [12]. In a joint effort by the projects FAMOUS and EMPIR Met4FoF it was demonstrated how an ontology of a sensor network could be utilized for an automated analysis [7], [13].…”

Fundamental Aspects in Data Analysis for Sensor Network Metrology

“…For instance, a machine-readable digital calibration certificate [10] could be provided by the itself, e.g., using OPC-UA, or from another source, e.g., an internal quality management platform. If needed, this information could be further extended by other data which could affect the quality of measurement [11].…”