Exchanging uncertainty: interoperable geostatistics?

Matthew Williams, Dan Cornford, Lucy Bastin, Benjamin R. Ingram

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Traditionally, geostatistical algorithms are contained within specialist GIS and spatial statistics software. Such packages are often expensive, with relatively complex user interfaces and steep learning curves, and cannot be easily integrated into more complex process chains. In contrast, Service Oriented Architectures (SOAs) promote interoperability and loose coupling within distributed systems, typically using XML (eXtensible Markup Language) and Web services. Web services provide a mechanism for a user to discover and consume a particular process, often as part of a larger process chain, with minimal knowledge of how it works. Wrapping current geostatistical algorithms with a Web service layer would thus increase their accessibility, but raises several complex issues. This paper discusses a solution to providing interoperable, automatic geostatistical processing through the use of Web services, developed in the INTAMAP project (INTeroperability and Automated MAPping). The project builds upon Open Geospatial Consortium standards for describing observations, typically used within sensor webs, and employs Geography Markup Language (GML) to describe the spatial aspect of the problem domain. Thus the interpolation service is extremely flexible, being able to support a range of observation types, and can cope with issues such as change of support and differing error characteristics of sensors (by utilising descriptions of the observation process provided by SensorML). XML is accepted as the de facto standard for describing Web services, due to its expressive capabilities which allow automatic discovery and consumption by ‘naive’ users. Any XML schema employed must therefore be capable of describing every aspect of a service and its processes. However, no schema currently exists that can define the complex uncertainties and modelling choices that are often present within geostatistical analysis. We show a solution to this problem, developing a family of XML schemata to enable the description of a full range of uncertainty types. These types will range from simple statistics, such as the kriging mean and variances, through to a range of probability distributions and non-parametric models, such as realisations from a conditional simulation. By employing these schemata within a Web Processing Service (WPS) we show a prototype moving towards a truly interoperable geostatistical software architecture.
Original languageEnglish
Title of host publicationgeoENV VII – Geostatistics for Environmental Applications
PublisherSpringer
Pages321-331
Number of pages11
Volume16
ISBN (Print)9789048123216
DOIs
Publication statusPublished - 2008

Fingerprint

XML
Web services
Interoperability
Statistics
Markup languages
Sensors
Software architecture
Service oriented architecture (SOA)
Processing
Geographic information systems
Probability distributions
User interfaces
Interpolation
Uncertainty

Bibliographical note

geoENV 2008, 8-10 September 2008, Southampton (UK). The original publication is available at www.springerlink.com

Keywords

  • automatic geostatistical processing
  • Web services
  • INTAMAP project
  • Open Geospatial Consortium standards
  • describing observations
  • sensor webs
  • Geography Markup Language
  • GML
  • interpolation service
  • change of support
  • error characteristics of sensors

Cite this

Williams, M., Cornford, D., Bastin, L., & Ingram, B. R. (2008). Exchanging uncertainty: interoperable geostatistics? In geoENV VII – Geostatistics for Environmental Applications (Vol. 16, pp. 321-331). Springer. https://doi.org/10.1007/978-90-481-2322-3_28
Williams, Matthew ; Cornford, Dan ; Bastin, Lucy ; Ingram, Benjamin R. / Exchanging uncertainty: interoperable geostatistics?. geoENV VII – Geostatistics for Environmental Applications. Vol. 16 Springer, 2008. pp. 321-331
@inbook{d1d71e2012ac4e89afcdba605b121bbd,
title = "Exchanging uncertainty: interoperable geostatistics?",
abstract = "Traditionally, geostatistical algorithms are contained within specialist GIS and spatial statistics software. Such packages are often expensive, with relatively complex user interfaces and steep learning curves, and cannot be easily integrated into more complex process chains. In contrast, Service Oriented Architectures (SOAs) promote interoperability and loose coupling within distributed systems, typically using XML (eXtensible Markup Language) and Web services. Web services provide a mechanism for a user to discover and consume a particular process, often as part of a larger process chain, with minimal knowledge of how it works. Wrapping current geostatistical algorithms with a Web service layer would thus increase their accessibility, but raises several complex issues. This paper discusses a solution to providing interoperable, automatic geostatistical processing through the use of Web services, developed in the INTAMAP project (INTeroperability and Automated MAPping). The project builds upon Open Geospatial Consortium standards for describing observations, typically used within sensor webs, and employs Geography Markup Language (GML) to describe the spatial aspect of the problem domain. Thus the interpolation service is extremely flexible, being able to support a range of observation types, and can cope with issues such as change of support and differing error characteristics of sensors (by utilising descriptions of the observation process provided by SensorML). XML is accepted as the de facto standard for describing Web services, due to its expressive capabilities which allow automatic discovery and consumption by ‘naive’ users. Any XML schema employed must therefore be capable of describing every aspect of a service and its processes. However, no schema currently exists that can define the complex uncertainties and modelling choices that are often present within geostatistical analysis. We show a solution to this problem, developing a family of XML schemata to enable the description of a full range of uncertainty types. These types will range from simple statistics, such as the kriging mean and variances, through to a range of probability distributions and non-parametric models, such as realisations from a conditional simulation. By employing these schemata within a Web Processing Service (WPS) we show a prototype moving towards a truly interoperable geostatistical software architecture.",
keywords = "automatic geostatistical processing, Web services, INTAMAP project, Open Geospatial Consortium standards, describing observations, sensor webs, Geography Markup Language, GML, interpolation service, change of support, error characteristics of sensors",
author = "Matthew Williams and Dan Cornford and Lucy Bastin and Ingram, {Benjamin R.}",
note = "geoENV 2008, 8-10 September 2008, Southampton (UK). The original publication is available at www.springerlink.com",
year = "2008",
doi = "10.1007/978-90-481-2322-3_28",
language = "English",
isbn = "9789048123216",
volume = "16",
pages = "321--331",
booktitle = "geoENV VII – Geostatistics for Environmental Applications",
publisher = "Springer",
address = "Germany",

}

Williams, M, Cornford, D, Bastin, L & Ingram, BR 2008, Exchanging uncertainty: interoperable geostatistics? in geoENV VII – Geostatistics for Environmental Applications. vol. 16, Springer, pp. 321-331. https://doi.org/10.1007/978-90-481-2322-3_28

Exchanging uncertainty: interoperable geostatistics? / Williams, Matthew; Cornford, Dan; Bastin, Lucy; Ingram, Benjamin R.

geoENV VII – Geostatistics for Environmental Applications. Vol. 16 Springer, 2008. p. 321-331.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - Exchanging uncertainty: interoperable geostatistics?

AU - Williams, Matthew

AU - Cornford, Dan

AU - Bastin, Lucy

AU - Ingram, Benjamin R.

N1 - geoENV 2008, 8-10 September 2008, Southampton (UK). The original publication is available at www.springerlink.com

PY - 2008

Y1 - 2008

N2 - Traditionally, geostatistical algorithms are contained within specialist GIS and spatial statistics software. Such packages are often expensive, with relatively complex user interfaces and steep learning curves, and cannot be easily integrated into more complex process chains. In contrast, Service Oriented Architectures (SOAs) promote interoperability and loose coupling within distributed systems, typically using XML (eXtensible Markup Language) and Web services. Web services provide a mechanism for a user to discover and consume a particular process, often as part of a larger process chain, with minimal knowledge of how it works. Wrapping current geostatistical algorithms with a Web service layer would thus increase their accessibility, but raises several complex issues. This paper discusses a solution to providing interoperable, automatic geostatistical processing through the use of Web services, developed in the INTAMAP project (INTeroperability and Automated MAPping). The project builds upon Open Geospatial Consortium standards for describing observations, typically used within sensor webs, and employs Geography Markup Language (GML) to describe the spatial aspect of the problem domain. Thus the interpolation service is extremely flexible, being able to support a range of observation types, and can cope with issues such as change of support and differing error characteristics of sensors (by utilising descriptions of the observation process provided by SensorML). XML is accepted as the de facto standard for describing Web services, due to its expressive capabilities which allow automatic discovery and consumption by ‘naive’ users. Any XML schema employed must therefore be capable of describing every aspect of a service and its processes. However, no schema currently exists that can define the complex uncertainties and modelling choices that are often present within geostatistical analysis. We show a solution to this problem, developing a family of XML schemata to enable the description of a full range of uncertainty types. These types will range from simple statistics, such as the kriging mean and variances, through to a range of probability distributions and non-parametric models, such as realisations from a conditional simulation. By employing these schemata within a Web Processing Service (WPS) we show a prototype moving towards a truly interoperable geostatistical software architecture.

AB - Traditionally, geostatistical algorithms are contained within specialist GIS and spatial statistics software. Such packages are often expensive, with relatively complex user interfaces and steep learning curves, and cannot be easily integrated into more complex process chains. In contrast, Service Oriented Architectures (SOAs) promote interoperability and loose coupling within distributed systems, typically using XML (eXtensible Markup Language) and Web services. Web services provide a mechanism for a user to discover and consume a particular process, often as part of a larger process chain, with minimal knowledge of how it works. Wrapping current geostatistical algorithms with a Web service layer would thus increase their accessibility, but raises several complex issues. This paper discusses a solution to providing interoperable, automatic geostatistical processing through the use of Web services, developed in the INTAMAP project (INTeroperability and Automated MAPping). The project builds upon Open Geospatial Consortium standards for describing observations, typically used within sensor webs, and employs Geography Markup Language (GML) to describe the spatial aspect of the problem domain. Thus the interpolation service is extremely flexible, being able to support a range of observation types, and can cope with issues such as change of support and differing error characteristics of sensors (by utilising descriptions of the observation process provided by SensorML). XML is accepted as the de facto standard for describing Web services, due to its expressive capabilities which allow automatic discovery and consumption by ‘naive’ users. Any XML schema employed must therefore be capable of describing every aspect of a service and its processes. However, no schema currently exists that can define the complex uncertainties and modelling choices that are often present within geostatistical analysis. We show a solution to this problem, developing a family of XML schemata to enable the description of a full range of uncertainty types. These types will range from simple statistics, such as the kriging mean and variances, through to a range of probability distributions and non-parametric models, such as realisations from a conditional simulation. By employing these schemata within a Web Processing Service (WPS) we show a prototype moving towards a truly interoperable geostatistical software architecture.

KW - automatic geostatistical processing

KW - Web services

KW - INTAMAP project

KW - Open Geospatial Consortium standards

KW - describing observations

KW - sensor webs

KW - Geography Markup Language

KW - GML

KW - interpolation service

KW - change of support

KW - error characteristics of sensors

UR - http://www.springerlink.com/content/r2w144l7613j3q67/about/

U2 - 10.1007/978-90-481-2322-3_28

DO - 10.1007/978-90-481-2322-3_28

M3 - Chapter

SN - 9789048123216

VL - 16

SP - 321

EP - 331

BT - geoENV VII – Geostatistics for Environmental Applications

PB - Springer

ER -

Williams M, Cornford D, Bastin L, Ingram BR. Exchanging uncertainty: interoperable geostatistics? In geoENV VII – Geostatistics for Environmental Applications. Vol. 16. Springer. 2008. p. 321-331 https://doi.org/10.1007/978-90-481-2322-3_28