Provenance in Sensor Data Management

Provenance In Sensor Data Management: A Cohesive, Independent Solution

Sensor Data Management, Validation, Correction, and Provenance for Building Technologies

Oak Ridge National Laboratory (ORNL) conducts research on technologies that use a wide range of sensors to develop and characterize building energy performance. The management of high-resolution sensor data, analysis, and tracing lineage of such activities is challenging. Missing or corrupt data due to sensor failure, fouling, drifting, calibration error, or data logger failure is another issue...

Provenance Aware Linked Sensor Data

Provenance, from the French word “provenir”, describes the lineage or history of a data entity. Provenance is critical information in the sensors domain to identify a sensor and analyze the observation data over time and geographical space. In this paper, we present a framework to model and query the provenance information associated with the sensor data exposed as part of the Web of Data using...

Data Provenance and Reliability in Sensor Networks

Promoting the capture of sensor data provenance: a role-based approach to enable data quality assessment, sensor management and interoperability

Sensor technologies and capabilities have an effect on observational data quality. Typically, data management begins, at best, when a data manager obtains the data and needs to describe it sufficiently to data consumers. Often, the sensing methods are not adequately described and the data manager does not know the appropriate questions to ask or where to direct questions about sensors, their co...