Leveraging the Open Provenance Model as a Multi-tier Model for Global Climate Research

Stephan, Eric G.; Halter, Todd D.; Ermold, Brian

doi:10.1007/978-3-642-17819-1_5

Cited by 7 publications

(5 citation statements)

References 6 publications

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“…Having this motivation, provenance should be more deeply studied by sensor networks community. Some research has leveraged provenance in fault recovery and success validation , in troubleshooting, and bug finding . In some research, provenance information associated with sensor data has been used in answering domain‐specific complex queries .…”

Section: Related Workmentioning

confidence: 99%

ProTru: a provenance‐based trust architecture for wireless sensor networks

Doğan

2016

Int J Network Mgmt

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Summary Trust is an important component of wireless sensor networks for believability of the produced data, and trust history is a crucial asset in deciding trust of the data. In this paper, we show how provenance can be used for registering previous trust records and other information such as node type, data type, and node location. Our aim is to design a distributed trust‐enhancing architecture using only local provenance during sensor fusion with a low communication overhead. Our network is cognitive in the sense that our system reacts automatically upon detecting low trust. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Related Workmentioning

confidence: 99%

ProTru: a provenance‐based trust architecture for wireless sensor networks

Doğan

2016

Int J Network Mgmt

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“…Benefited from Semantic Web, these models can support data linkage and multi-granularity provenance generated in heterogeneous environments. Provenance granularity has been studied in [1,6,[8][9][10]12]. Granularities are constructed from users' perspectives, and limited to specified application domains.…”

Section: Related Workmentioning

confidence: 99%

Semantic Similarity of Workflow Traces with Various Granularities

Liu

Bai

Yang

2016

Web Information Systems Engineering – WISE 2016

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A workflow trace describes provenance information of a particular workflow execution. Understanding workflow traces and their similarity have many applications in both scientific research and business world. Given workflow traces generated by heterogeneous systems with difference granularities, it is a challenge for users to understand their similarities. In this work, we investigate workflow traces' granularity problem and their similarity method. Algorithms are developed to transform a trace into its multi-granularity forms assisting by a workflow trace ontology; A novel generic semantic similarity algorithm is proposed that not only considers the structural similarity but also the semantics coverage embedded in traces during transformation. Furthermore, theoretical analysis is presented to compute the maximum and minimum semantic similarity; Our approach enables the two workflow traces can be compared with any granularity. The experiment using real world workflow traces demonstrates the effectiveness of the proposed methods.

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“…Different techniques have been used to model provenance granularities. Stephan et al [16] presents a multi-tier provenance model in which each tier has a unique purpose, different characteristics, and distinct levels of granularity. They use the Open Provenance Model (OPM) to encode their provenance and disseminate higher level provenance that are abstracted from provenance captured in different tiers, e.g.…”

Section: Related Workmentioning

confidence: 99%

Towards Unified Provenance Granularities

Lebo

Wang

Graves

et al. 2012

Lecture Notes in Computer Science

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As Open Data becomes commonplace, methods are needed to integrate disparate data from a variety of sources. Although Linked Data design has promise for integrating world wide data, integrators often struggle to provide appropriate transparency for their sources and transformations. Without this transparency, cautious consumers are unlikely to find enough information to allow them to trust third party content. While capturing provenance in RPI's Linking Open Government Data project, we were faced with the common problem that only a portion of provenance that is captured is effectively used. Using our water quality portal's use case as an example, we argue that one key to enabling provenance use is a better treatment of provenance granularity. To address this challenge, we have designed an approach that supports deriving abstracted provenance from granular provenance in an open environment. We describe the approach, show how it addresses the naturally occurring unmet provenance needs in a family of applications, and describe how the approach addresses similar problems in open provenance and open data environments.

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Leveraging the Open Provenance Model as a Multi-tier Model for Global Climate Research

Cited by 7 publications

References 6 publications

ProTru: a provenance‐based trust architecture for wireless sensor networks

ProTru: a provenance‐based trust architecture for wireless sensor networks

Semantic Similarity of Workflow Traces with Various Granularities

Towards Unified Provenance Granularities

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