Case Study: GeoFrame software helps Geoscience Australia provide quick access to 2D and 3D seismic survey data within newly released license/permit in support of successful Australian Acreage Release bidding rounds

Legacy product - no abstract available

Discusses reasons to use the Australian Stratigraphic Units Database (ASUD), and new features of the web query page and reports

This dataset contains species identifications of sponges collected during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a benthic sled. Specimens were lodged at Northern Territory Museum on the 26 September 2009. Species-level identifications were undertaken by Belinda Glasby at the Northern Territory Museum and were delivered to Geoscience Australia on the 23 February 2011. See GA Record 2010/09 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.

The Australian National Gravity Database (ANGD) contains over 1.8 million gravity observations from over 2,000 surveys conducted in Australia over the last 80 years. Three processes are required to correct these observations for the effects of the surrounding topography: firstly a Bouguer correction (Bullard A), which approximates the topography as an infinite horizontal slab; secondly a correction to that horizontal slab for the curvature of the Earth (Bullard B); and thirdly a terrain correction (Bullard C), which accounts for the undulations in the surrounding topography. These three corrections together produce complete bouguer anomalies. Since February 2008, a spherical cap bouguer anomaly calculation has been applied to data extracted from the ANGD. This calculation applies the Bullard A and Bullard B corrections. Terrain corrections, Bullard C, have now been calculated for all terrestrial gravity observations in the ANGD allowing the calculation of complete bouguer anomalies. These terrain corrections were calculated using the Shuttle Radar Topography Mission 3 arc-second digital elevation data. The complete bouguer anomalies calculated for the ANGD provide users of the data with a more accurate representation of crustal density variations through the application of a more accurate Earth model to the gravity observations.

Scientific data are being generated at an ever increasing rate. Existing volumes of data can no longer be effectively processed by humans, and efficient and timely processing by computers requires development of standardised machine readable formats and interfaces. Although there is also a growing need to share data, information and services across multiple disciplines, many standards currently being developed tend to be discipline specific. To enable cross-disciplinary research a more modular approach to standards development is required so that common components (e.g., location, units of measure, geometric shape, instrument type, etc) can be identified and standardised across all disciplines. Already international standards bodies such as ISO and OGC (Open Geospatial Consortium) are well advanced in developing technical standards that are applicable for interchange of some of these common components such as GML (Geography Markup Language), Observations and Measurements Encoding Standard, SensorML, Spatial Coordinate Systems, Metadata Standards, etc. However the path for developing the remaining discipline specific and discipline independent standards is less coordinated. There is a clear lack of infrastructure and governance not only for the development of the required standards but also for storage, maintenance and extension of these standards over time. There is also no formal mechanism to harmonise decisions made by the various scientific disciplines to avoid unwanted overlap. The National Committee for Data in Science (NCDS) was established in 2008 by the Australian Academy of Science to provide an interdisciplinary focus for scientifc data management. In 2008 an informal request from the NCDS was put to the international Committee on Data for Science and Technology (CODATA) to consider taking on a new coordination role on issues related to the development and governance of standards required for the discovery of, and access to digital scientific data.

GeoSciML v3 (www.geosciml.org) and EarthResourceML v2 (www.earthresourceml.org) are the latest releases of geoscience data transfer standards from the IUGS-CGI Interoperability Working Group (IWG). The data standards each comprise a UML model and complex features GML schemas, extending the spatial standards of the Open Geospatial Consortium (OGC), including GML v3.2, O&M v2, and SWE Common v2. Future development of GeoSciML and EarthResourceML will occur under a collaborative IUGS-OGC arrangement. GeoSciML covers a wide range of geological data, including geological units, structures, earth materials, boreholes, geomorphology, petrophysical properties, and sampling and analytical metadata. The model was refactored from a single application schema in version 2 into a number of smaller, more manageable schemas in version 3. EarthResourceML covers solid earth resources (mineral occurrences, resources and reserves) and their exploitation (mines and mining activities). The model has been extended to accommodate the requirements of the EU INSPIRE data sharing initiative, seeing the addition of mineral exploration activity and environmental aspects (ie, mining waste) to the model. GeoSciML-Portrayal is a simple-features GML application schema based on a simplified core of GeoSciML. It supports presentation of geological map units, contacts, and faults in Web Map Services, and provides a link between simple-feature data delivery and more complex GeoSciML WFS services. The schema establishes naming conventions for fields commonly used to symbolize geological maps to enable visual harmonization of map services. The IWG have established a vocabulary service at http://resource.geosciml.org, serving geoscience vocabularies in RDF-SKOS format. Vocabularies are not included in GeoSciML and EarthResourceML, but the models recommend a standard pattern to reference controlled vocabularies using HTTP-URI links. GeoSciML and EarthResourceML have been adopted or recommended as the data exchange standards in key international interoperability initiatives, including OneGeology, the INSPIRE project, the US Geoscience Information Network, and the Australia/NZ Government Geoscience Information Committee.

Geoscience Australia is supporting the exploration and development of offshore oil and gas resources and establishment of Australia's national representative system of marine protected areas through provision of spatial information about the physical and biological character of the seabed. Central to this approach is prediction of Australia's seabed biodiversity from spatially continuous data of physical seabed properties. However, information for these properties is usually collected at sparsely-distributed discrete locations, particularly in the deep ocean. Thus, methods for generating spatially continuous information from point samples become essential tools. Such methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Improving the accuracy of these physical data for biodiversity prediction, by searching for the most robust spatial interpolation methods to predict physical seabed properties, is essential to better inform resource management practises. In this regard, we conducted a simulation experiment to compare the performance of statistical and mathematical methods for spatial interpolation using samples of seabed mud content across the Australian margin. Five factors that affect the accuracy of spatial interpolation were considered: 1) region; 2) statistical method; 3) sample density; 4) searching neighbourhood; and 5) sample stratification by geomorphic provinces. Bathymetry, distance-to-coast and slope were used as secondary variables. In this study, we only report the results of the comparison of 14 methods (37 sub-methods) using samples of seabed mud content with five levels of sample density across the southwest Australian margin. The results of the simulation experiment can be applied to spatial data modelling of various physical parameters in different disciplines and have application to a variety of resource management applications for Australia's marine region.

This dataset contains species identifications of echinoderms collected during survey GA2476 (R.V. Solander, 12 August - 15 September 2008). Animals were collected from the Western Australian Margin with a BODO sediment grab or rock dredge. Specimens were lodged at Museum of Victoria on the 10 March 2009. Species-level identifications were undertaken by Tim O'Hara at the Museum of Victoria and were delivered to Geoscience Australia on the 24 April 2009. See GA Record 2009/02 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.

Open Geospatial Consortium (OGC) web services offer a cost efficient technology that permits transfer of standardised data from distributed sources, removing the need for data to be regularly uploaded to a centralised database. When combined with community defined exchange standards, the OGC services offer a chance to access the latest data from the originating agency and return the data in a consistent format. Interchange and mark-up languages such as the Geography Markup Language (GML) provide standard structures for transferring geospatial information over the web. The IUGS Commission for the Management and Application of Geoscience Information (CGI) has an on-going collaborative project to develop a data model and exchange language based on GML for geological map and borehole data, the GeoScience Mark-up Language (GeoSciML). The Australian Government Geoscience Information Committee (GGIC) has used the GeoSciML model as a basis to cover mineral resources (EarthResourceML), and the Canadian Groundwater Information Network (GIN) has extended GeoSciML into the groundwater domain (GWML). The focus of these activities is to develop geoscience community schema that use globally accepted geospatial web service data exchange standards.