Geographic information systems form a core part of Earth Science education and teaching, allowing the ever-growing repositories of digital geo-data to be integrated and visualised in a unified fashion. These systems cope with the wide variety of spatial data types, each with their own properties and metadata, allowing for a better understanding of how Earth processes operate. A unique requirement for the Earth Sciences is to take into account plate motion and crustal deformation processes acting through time, thus altering the various spatial relationships. The open-source GPlates software (www.gplates.org) infrastructure has become a standard tool for this type of analysis, providing the ability to reconstruct various datasets through time interactively by attaching arbitrary data to tectonic plates. Combining vast datasets in this manner is increasing the analysis complexity, with traditional visualisation-based approaches becoming ineffective in extracting necessary information and discovering new insights. In addressing this, GPlates has been extended with two key technologies, manifesting itself as a powerful interactive knowledge-discovery platform. The first technology is a "data coregistration" tool, in which desired relationships between various datasets are recursively defined, thus providing the key link between a qualitative visualisation environment and a quantitative multivariate statistical analysis framework. The second technology is a data-mining environment (Orange, http://orange.biolab.si), better suited to coping with complexities due to large datasets, high dimensionality, spatial and temporal dynamics, different data types etc. The data-mining tool has a diverse library of components allowing for interactive filtering, combining, transforming and pattern analysis of incoming data. Attached to the data-mining tool is a visual-programming environment in which underlying software complexities are abstracted from the user, allowing for the rapid prototyping of analysis work-flows without requiring programming expertise. A plug-in framework allows for the construction of new spatio-temporal data processing components, which is seeing the functionality and flexibility of this environment increasing rapidly, aided by an open-source model. The resultant ensemble of technologies lends itself to becoming a frontier teaching and research tool, providing the necessary abstraction of complexity required to better understand how the various complex Earth processes acted through time resulting in the familiar spatial configuration we observe today.
AGU Fall Meeting Abstracts
- Pub Date:
- December 2011
- 1914 INFORMATICS / Data mining;
- 1928 INFORMATICS / GIS science;
- 1992 INFORMATICS / Virtual globes;
- 8149 TECTONOPHYSICS / Planetary tectonics