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Provenance Aware Linked Sensor Data

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Title Provenance Aware Linked Sensor Data
Author , , ,
Venue 2nd Workshop on Trust and Privacy on the Social and Semantic Web
Year 2010
Resource Type WorkshopPaper
Keyword(s) Semantic Sensor Web,Dataset Generation,Linked Data,provenir ontology,Sensor Web Enablement,Provenance Management Framework,Provenance,Lineage,Sensor Data,Resource Description Framework(RDF)
Full Citation Harshal Patni, Satya S. Sahoo, Cory Henson and Amit Sheth, 'Provenance Aware Linked Sensor Data', 2nd Workshop on Trust and Privacy on the Social and Semantic Web, Co-located with ESWC, Heraklion Greece, 30th May - 03 June 2010
Abstract 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 the Linked Open Data conventions. This is accomplished by developing an ontology-driven provenance management infrastructure that includes a representation model and query infrastructure. This provenance infrastructure, called Sensor Provenance Management System (PMS), is underpinned by a domain specific provenance ontology called Sensor Provenance (SP) ontology. The SP ontology extends the Provenir upper level provenance ontology to model domain-specific provenance in the sensor domain. In this paper, we describe the implementation of the Sensor PMS for provenance tracking in the Linked Sensor Data.
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