Full Meta Object profiling for flexible geoprocessing workflows

Rosser, Julian F.; Jackson, Mike; Leibovici, Didier

doi:10.1111/tgis.12460

Cited by 3 publications

(3 citation statements)

References 39 publications

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“…It is based upon a workflow editor that uses the Business Process Modelling Notation (BPMN) standard, a standard for graphical notation for specifying business processes (similar to a flow chart) www.bpmn.org. QAwAT enables the selection of QC tests by the stakeholder, which are then combined and chained to form a QA procedure for their CS survey [37,38]. To ensure interoperability, the QCs are implemented as Web Processing Service (WPS) processes.…”

Section: Quality Assurance and Quality Control Frameworkmentioning

confidence: 99%

Earth Observation for Citizen Science Validation, or Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations

Leibovici

Williams

Rosser

et al. 2017

Data

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Environmental policy involving citizen science (CS) is of growing interest. In support ofthis open data stream of information, validation or quality assessment of the CS geo-located data to their appropriate usage for evidence-based policy making needs a flexible and easily adaptable data curation process ensuring transparency. Addressing these needs, this paper describes an approach for automatic quality assurance as proposed by the Citizen OBservatory WEB (COBWEB) FP7 project. This approach is based upon a workflow composition that combines different quality controls, each belonging to seven categories or "pillars". Each pillar focuses on a specific dimension in the types of reasoning algorithms for CS data qualification. These pillars attribute values to a range of quality elements belonging to three complementary quality models. Additional data from various sources, such as Earth Observation (EO) data, are often included as part of the inputs of quality controls within the pillars. However, qualified CS data can also contribute to the validation of EO data. Therefore, the question of validation can be considered as "two sides of the same coin". Based on an invasive species CS study, concerning Fallopia japonica (Japanese knotweed), the paper discusses the flexibility and usefulness of qualifying CS data, either when using an EO data product for the validation within the quality assurance process, or validating an EO data product that describes the risk of occurrence of the plant. Both validation paths are found to be improved by quality assurance of the CS data. Addressing the reliability of CS open data, issues and limitations of the role of quality assurance for validation, due to the quality of secondary data used within the automatic workflow, are described, e.g., error propagation, paving the route to improvements in the approach.

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Section: Quality Assurance and Quality Control Frameworkmentioning

confidence: 99%

Earth Observation for Citizen Science Validation, or Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations

Leibovici

Williams

Rosser

et al. 2017

Data

Self Cite

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show abstract

“…It is based upon a workflow editor which uses the Business Process Modelling Notation (BPMN) standard, a standard for graphical notation for specifying business processes (similar to a flow chart) www.bpmn.org. QAwAT enables the selection of QC tests by the stakeholder, which are then combined and chained to form a QA procedure for their CS survey [37,38]. To ensure interoperability, the QCs are implemented as Web Processing Service (WPS) processes.…”

Section: Quality Assurance and Quality Control Frameworkmentioning

confidence: 99%

Earth Observation for Citizen Science Validation, or, Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations

Leibovici

Williams²,

Rosser

et al. 2017

Preprint

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27Based on an invasive species CS study, concerning Fallopia japonica (Japanese knotweed), the paper 28 discusses the flexibility and usefulness of qualifying CS data, either when using an EO data for the 29 validation within the quality assurance process, or validating an EO data product that describes the 30 risk of occurrence of the plant. Both validation paths are found to be improved by quality assurance 31 of the CS data. Addressing the reliability of CS open data, issues and limitations of the role of quality 32 assurance for validation, due to the quality of secondary data used within the automatic workflow, 33 are described, e.g. error propagation, paving the route to improvements in the approach. 34

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“…These techniques cannot only rely on syntactic aspects: they also need semantic aspects of the functional properties. The lack of semantics in service description using the WPS standard prevents the use of such a matching process and is therefore considered as one of the main limitations of GWS discovery [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Geospatial Web Services Discovery through Semantic Annotation of WPS

Halilali

Gouardères

Gaio

et al. 2022

IJGI

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This paper presents an approach to GWS (GeospatialWeb Service) discovery through the semantic annotation of WPS (Web Processing Service) service descriptions. The rationale behind this work is that search engines that use appropriate semantic-based similarity measures in the matching process are more accurate in terms of precision and recall than those based on syntactic matching alone. The lack of semantics in the description of services using a standard such as WPS prevents the use of such a matching process and is considered a limitation of GWS discovery. The GWS discovery approach presented is based on the consideration of semantics in the service description method and in the matching process. The description of services is based on a semantic lightweight meta-model instantiated in the WPS 2.0 standard, extending the description of the service through metadata tags. The matching process is performed in three steps (functionality matching step, I/O (Input/Output) matching step and non-functional matching step). Its core is a semantic similarity measure that combines logical and non-logical matching methods. Finally, the paper presents the results of an experiment applying the proposed discovery approach on a GWS corpus, showing promising results and the added value of the three-step matching process.

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Full Meta Object profiling for flexible geoprocessing workflows

Cited by 3 publications

References 39 publications

Earth Observation for Citizen Science Validation, or Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations

Earth Observation for Citizen Science Validation, or Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations

Earth Observation for Citizen Science Validation, or, Citizen Science for Earth Observation Validation? The Role of Quality Assurance of Volunteered Observations

Geospatial Web Services Discovery through Semantic Annotation of WPS

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