The GPlates Geological Information Model and Markup Language

Abstract

Abstract. Understanding tectonic and geodynamic processes leading to the present-day configuration of the Earth involves studying data and models across a variety of disciplines, from geochemistry, geochronology and geophysics, to plate kinematics and mantle dynamics. All these data represent a 3-D spatial and 1-D temporal framework, a formalism which is not exploited by traditional spatial analysis tools. This is arguably a fundamental limit in both the rigour and sophistication in which datasets can be combined for geological deep time analysis, and often confines the extent of data analyses to the present-day configurations of geological objects. The GPlates Geological Information Model (GPGIM) represents a formal specification of geological and geophysical data in a time-varying plate tectonics context, used by the GPlates virtual-globe software. It provides a framework in which relevant types of geological data are attached to a common plate tectonic reference frame, allowing the data to be reconstructed in a time-dependent spatio-temporal plate reference frame. The GPlates Markup Language (GPML), being an extension of the open standard Geography Markup Language (GML), is both the modelling language for the GPGIM and an XML-based data format for the interoperable storage and exchange of data modelled by it. The GPlates software implements the GPGIM allowing researchers to query, visualise, reconstruct and analyse a rich set of geological data including numerical raster data. The GPGIM has recently been extended to support time-dependent geo-referenced numerical raster data by wrapping GML primitives into the time-dependent framework of the GPGIM. Coupled with GPlates' ability to reconstruct numerical raster data and import/export from/to a variety of raster file formats, as well as its handling of time-dependent plate boundary topologies, interoperability with geodynamic softwares is established, leading to a new generation of deep-time spatio-temporal data analysis and modelling, including a variety of new functionalities, such as 4-D data-mining.