GeoSciML: Enabling the Exchange of Geological Map Data

Simons, Bruce; Boisvert, Eric; Brodaric, Boyan; Cox, Simon J.; Duffy, Tim; Johnson, Bruce R.; Laxton, John L.; Richard, Steve

doi:10.1071/aseg2006ab162

Cited by 18 publications

(15 citation statements)

References 3 publications

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“…in HDF5 formats), and a better link to geological data sets and parameters (e.g. through the use of GeoSciML, see Sen andDuffy, 2005 andSimons et al, 2006). In addition, we are actively working on developments of additional experiment classes, for example for detailed topological analyses of structural models, and further post-processing and uncertainty quantification methods.…”

Section: Discussionmentioning

confidence: 99%

pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling

et al. 2016

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Abstract. We present a novel methodology for performing experiments with subsurface structural models using a set of flexible and extensible Python modules. We utilize the ability of kinematic modelling techniques to describe major deformational, tectonic, and magmatic events at low computational cost to develop experiments testing the interactions between multiple kinematic events, effect of uncertainty regarding event timing, and kinematic properties. These tests are simple to implement and perform, as they are automated within the Python scripting language, allowing the encapsulation of entire kinematic experiments within high-level class definitions and fully reproducible results. In addition, we provide a link to geophysical potential-field simulations to evaluate the effect of parameter uncertainties on maps of gravity and magnetics. We provide relevant fundamental information on kinematic modelling and our implementation, and showcase the application of our novel methods to investigate the interaction of multiple tectonic events on a pre-defined stratigraphy, the effect of changing kinematic parameters on simulated geophysical potential fields, and the distribution of uncertain areas in a full 3-D kinematic model, based on estimated uncertainties in kinematic input parameters. Additional possibilities for linking kinematic modelling to subsequent process simulations are discussed, as well as additional aspects of future research. Our modules are freely available on github, including documentation and tutorial examples, and we encourage the contribution to this project.

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Section: Discussionmentioning

confidence: 99%

pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling

et al. 2016

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“…Such a model allows common description of geologic features leading to interoperability through a markup language for data interchange for the discovery and utilization of globally distributed geoscience data and information. GeoSciML is a critical first step in the use of informatics-based technologies (Simons et al, 2006). 2.…”

Section: Why Do We Need Geoinformatics?mentioning

confidence: 99%

Geoinformatics: Transforming data to knowledge for geosciences

Sinha¹,

Malik²,

Rezgui³

et al. 2010

GSAT

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An integrative view of Earth as a system, based on multidisciplinary data, has become one of the most compelling reasons for research and education in the geosciences. It is now necessary to establish a modern infrastructure that can support the transformation of data to knowledge. Such an information infrastructure for geosciences is contained within the emerging science of geoinformatics, which seeks to promote the utilization and integration of complex, multidisciplinary data in seeking solutions to geoscience-based societal challenges.

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“…The Observations and Sampling models are imported and used in the GeoSciML information model that has been developed by the Interoperability Working Group of the IUGS Commission for Geoscience Information (Simons et al, 2006;Laxton and Wyborn, 2007) and is to be used in the OneGeology project (Jackson and Wyborn, 2007).…”

Section: Information Modelmentioning

confidence: 99%