Sensor data provenance: SSNO and PROV-O together at last

Michael Compton; David Corsar; Kerry Taylor

Sensor data provenance: SSNO and PROV-O together at last

Michael Compton
, David Corsar
, Kerry Taylor

Research output: Contribution to journal › Conference article › peer-review

9 Citations (Scopus)

Abstract

This paper presents an alignment between the W3C ProvenanceWorking Group's recommended ontology (PROV-O) and the W3C Semantic Sensor Networks Incubator Group's ontology (SSNO). The alignment views PROV-O as an upper ontology which is extended with SSNO concepts and properties. This allows representation of observation details and sensor deployments that are not possible in the SSNO alone, and gives a basis for alignment with Open Geospatial Consortium Observations & Measurements aligned ontologies. Further to the alignment, rules are presented that further constrain the interpretation of the aligned ontologies and provide a mechanism by which provenance information can be generated from SSN data thereby allowing modellers to take advantage of the new features. The benefit of the aligned ontologies is illustrated with an example of cross-domain provenance querying enabled by the alignment.

Original language	English
Pages (from-to)	67-82
Number of pages	16
Journal	CEUR Workshop Proceedings
Volume	1401
Publication status	Published - 2014
Event	Terra Cognita - Semantic Sensor Networks, TC-SSN 2014 - 6th International Workshop on the Foundations, Technologies and Applications of the Geospatial Web and 7th International Workshop on Semantic Sensor Networks, co-located with 13th International Semantic Web Conference, ISWC 2014 - Riva del Garda, Trentino, Italy Duration: 20 Oct 2014 → …

Cite this

@article{4f4de42c756e4328841fc79882292e79,

title = "Sensor data provenance: SSNO and PROV-O together at last",

abstract = "This paper presents an alignment between the W3C ProvenanceWorking Group's recommended ontology (PROV-O) and the W3C Semantic Sensor Networks Incubator Group's ontology (SSNO). The alignment views PROV-O as an upper ontology which is extended with SSNO concepts and properties. This allows representation of observation details and sensor deployments that are not possible in the SSNO alone, and gives a basis for alignment with Open Geospatial Consortium Observations \& Measurements aligned ontologies. Further to the alignment, rules are presented that further constrain the interpretation of the aligned ontologies and provide a mechanism by which provenance information can be generated from SSN data thereby allowing modellers to take advantage of the new features. The benefit of the aligned ontologies is illustrated with an example of cross-domain provenance querying enabled by the alignment.",

author = "Michael Compton and David Corsar and Kerry Taylor",

year = "2014",

language = "English",

volume = "1401",

pages = "67--82",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

publisher = "CEUR-WS",

note = "Terra Cognita - Semantic Sensor Networks, TC-SSN 2014 - 6th International Workshop on the Foundations, Technologies and Applications of the Geospatial Web and 7th International Workshop on Semantic Sensor Networks, co-located with 13th International Semantic Web Conference, ISWC 2014 ; Conference date: 20-10-2014",

}

TY - JOUR

T1 - Sensor data provenance

T2 - Terra Cognita - Semantic Sensor Networks, TC-SSN 2014 - 6th International Workshop on the Foundations, Technologies and Applications of the Geospatial Web and 7th International Workshop on Semantic Sensor Networks, co-located with 13th International Semantic Web Conference, ISWC 2014

AU - Compton, Michael

AU - Corsar, David

AU - Taylor, Kerry

PY - 2014

Y1 - 2014

N2 - This paper presents an alignment between the W3C ProvenanceWorking Group's recommended ontology (PROV-O) and the W3C Semantic Sensor Networks Incubator Group's ontology (SSNO). The alignment views PROV-O as an upper ontology which is extended with SSNO concepts and properties. This allows representation of observation details and sensor deployments that are not possible in the SSNO alone, and gives a basis for alignment with Open Geospatial Consortium Observations & Measurements aligned ontologies. Further to the alignment, rules are presented that further constrain the interpretation of the aligned ontologies and provide a mechanism by which provenance information can be generated from SSN data thereby allowing modellers to take advantage of the new features. The benefit of the aligned ontologies is illustrated with an example of cross-domain provenance querying enabled by the alignment.

AB - This paper presents an alignment between the W3C ProvenanceWorking Group's recommended ontology (PROV-O) and the W3C Semantic Sensor Networks Incubator Group's ontology (SSNO). The alignment views PROV-O as an upper ontology which is extended with SSNO concepts and properties. This allows representation of observation details and sensor deployments that are not possible in the SSNO alone, and gives a basis for alignment with Open Geospatial Consortium Observations & Measurements aligned ontologies. Further to the alignment, rules are presented that further constrain the interpretation of the aligned ontologies and provide a mechanism by which provenance information can be generated from SSN data thereby allowing modellers to take advantage of the new features. The benefit of the aligned ontologies is illustrated with an example of cross-domain provenance querying enabled by the alignment.

UR - https://www.scopus.com/pages/publications/84940100747

M3 - Conference article

AN - SCOPUS:84940100747

SN - 1613-0073

VL - 1401

SP - 67

EP - 82

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

Y2 - 20 October 2014

ER -

Sensor data provenance: SSNO and PROV-O together at last

Abstract

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