Lesley Wyborn

Lachlan Fold Belt granites revisited: high- and low-temperature granites and their implications

Many of the granites in southeastern Australia possess compositional, petrographic, zircon age inheritance and other features that cannot be accounted for satisfactorily by the classical models of petrogenesis. The restite model was developed to account for these features and recognises that unmelted but magmatically equilibrated source material (restite) may be entrained in a partial melt, together comprising magma. Variation in the degree of separation of those two components, leading to differences in the ratio of melt to restite, is responsible for the variation in composition within many suites of granites. A popular alternative view, that variation within suites resulted from magma mixing or mingling, conflicts with simple observations of the rock compositions and cannot be sustained. Several strong arguments can be made against another alternative view that fractional crystallisation was the dominant process in producing variation within those suites. New and conclusive evidence against that process is provided by the fact that zircon age inheritance is present in most of these granites where that has been examined. That has shown that the S‐type and most of the I‐type granites formed at low magmatic temperatures and confirmed that the compositional variation within those suites must have resulted from restite fractionation. The Ordovician sedimentary rocks exposed in the Lachlan Fold Belt are not sufficiently feldspathic to have produced the voluminous S‐type granites and volcanic rocks of the Bullenbalong Supersuite. The view that those granites and volcanic rocks were derived from more feldspathic metasedimentary rocks is supported by much evidence and confirmed by the fact that the pelitic enclaves in those granites are relatively high in Ca. The presence of a once‐thick metasedimentary basement in those areas in which these S‐type granites occur is inferred. The I‐type granites of the Lachlan belt are not compositionally analogous to the more calcic and less potassic granites found in younger subduction‐related continental margins and mostly formed at low magmatic temperatures through the partial melting of pre‐existing quartzo‐feldspathic igneous crust. This implies that the petrological evolution of the belt during the Silurian and Devonian occurred dominantly by the vertical redistribution of the components of older crust through partial melting and movement of granite magmas. Evolution of the belt at that time was not related to active subduction.

Chemistry of the Ordovician and Silurian greywackes of the Snowy Mountains, southeastern Australia: An example of chemical evolution of sediments with time

Abstract The Ordovician quartz-rich greywackes of the Snowy Mountains region are essentially mixtures of two components. These are quartz and clay minerals. The chemistry of any rock is largely determined by its proportions of clay minerals so that there is a strong negative correlation between Si and those elements, other than Si, contained in clay minerals. Elements that occur only in feldspar, but not in clay minerals, that is Ca, Na, Sr and Pb, have a low and variable concentration. These four elements have even lower abundances in the Silurian greywackes deposited in basins on a basement of the Ordovician rocks. This is interpreted to have resulted from a further cycle of chemical weathering that acted on Ordovician source rocks to produce the Silurian detritus. In a similar fashion, the Ordovician rocks are thought to have formed by weathering of more feldspar-rich sedimentary rocks at the margins of the Lachlan Fold Belt. Two episodes of chemical weathering are therefore recognised. The first produced the feldspar-poor Ordovician rocks; the second acted on part of these to form the almost feldspar-free Silurian strata. In both cases, Ca, Na, Sr and Pb were lost as feldspars were converted to clay minerals.

Age of Cu‐Au mineralisation, Cloncurry district, eastern Mt Isa Inlier, Queensland, as determined by 40Ar/39Ar dating∗

The 40Ar/39Ar dating of alteration biotite, muscovite and amphibole from a number of post‐peak metamorphic Cu‐Au deposits and alteration systems in the Cloncurry district, north Queensland has determined the timing of mineralisation and hydrothermal activity. Alteration biotite from the Ernest Henry Cu‐Au, Starra Au‐Cu, and Mt Elliott Cu‐Au deposits, sericite associated with hematite breccias in the Wimberu Granite, muscovite from an albitite pipe that intrudes the Gilded Rose Breccia, and sericite from a granitoid near the Osborne Cu‐Au deposit, yield ages which are broadly contemporaneous with the late ca 1510–1485 Ma phases of the Williams and Naraku Batholiths. Hornblende and biotite alteration, which pre‐date Cu‐Au mineralisation at Osborne, give a maximum age of ca 1540 Ma for the deposit, which is also a probable minimum age for peak metamorphism. Metamorphic minerals from the vicinity of Osborne yield dates which are significantly older (ca 1590–1570 Ma) than those from the hydrothermal phases. Da...

Rapid, high-resolution detection of environmental change over continental scales from satellite data – the Earth Observation Data Cube

ABSTRACT The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations – the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.

The NCI High Performance Computing and High Performance Data Platform to Support the Analysis of Petascale Environmental Data Collections

The National Computational Infrastructure (NCI) at the Australian National University (ANU) has co-located a priority set of over 10 PetaBytes (PBytes) of national data collections within a HPC research facility. The facility provides an integrated high-performance computational and storage platform, or a High Performance Data (HPD) platform, to serve and analyse the massive amounts of data across the spectrum of environmental collections – in particular from the climate, environmental and geoscientific domains. The data is managed in concert with the government agencies, major academic research communities and collaborating overseas organisations. By co-locating the vast data collections with high performance computing environments and harmonising these large valuable data assets, new opportunities have arisen for Data-Intensive interdisciplinary science at scales and resolutions not hitherto possible.

A Data Quality Strategy to Enable FAIR, Programmatic Access across Large, Diverse Data Collections for High Performance Data Analysis

To ensure seamless, programmatic access to data for High Performance Computing (HPC) and analysis across multiple research domains, it is vital to have a methodology for standardization of both data and services. At the Australian National Computational Infrastructure (NCI) we have developed a Data Quality Strategy (DQS) that currently provides processes for: (1) Consistency of data structures needed for a High Performance Data (HPD) platform; (2) Quality Control (QC) through compliance with recognized community standards; (3) Benchmarking cases of operational performance tests; and (4) Quality Assurance (QA) of data through demonstrated functionality and performance across common platforms, tools and services. By implementing the NCI DQS, we have seen progressive improvement in the quality and usefulness of the datasets across the different subject domains, and demonstrated the ease by which modern programmatic methods can be used to access the data, either in situ or via web services, and for uses ranging from traditional analysis methods through to emerging machine learning techniques. To help increase data re-usability by broader communities, particularly in high performance environments, the DQS is also used to identify the need for any extensions to the relevant international standards for interoperability and/or programmatic access.

Graph Connections Made By RD-Switchboard Using NCI's Metadata

This paper demonstrates the connectivity graphs made by Research Data Switchboard (RD-Switchboard) using NCIs metadata database. Making research data connected, discoverable and reusable are some of the key enablers of the new data revolution in research. We show how the Research Data Switchboard identified the missing critical information in our database, and what improvements have been made by this system. The connections made by the RD-Switchboard demonstrated the various use of the datasets, and the network of researchers and cross-referenced publications.

Supporting Data Reproducibility at NCI Using the Provenance Capture System

Scientific research is published in journals so that the research community is able to share knowledge and results, verify hypotheses, contribute evidence-based opinions and promote discussion. However, it is hard to fully understand, let alone reproduce, the results if the complex data manipulation that was undertaken to obtain the results are not clearly explained and/or the final data used is not available. Furthermore, the scale of research data assets has now exponentially increased to the point that even when available, it can be difficult to store and use these data assets. In this paper, we describe the solution we have implemented at the National Computational Infrastructure (NCI) whereby researchers can capture workflows, using a standards-based provenance representation. This provenance information, combined with access to the original dataset and other related information systems, allow datasets to be regenerated as needed which simultaneously addresses both result reproducibility and storage issues.

Providing Research Graph Data in JSON-LD Using Schema.org

In this position paper, we describe a pilot project that provides Research Graph records to external web services using JSON-LD. The Research Graph database contains a large-scale graph that links research datasets (i.e., data used to support research) to funding records (i.e. grants), publications and researcher records such as ORCID profiles. This database was derived from the work of the Research Data Alliance Working Group on Data Description Registry Interoperability (DDRI), and curated using the Research Data Switchboard open source software. By being available in Linked Data format, the Research Graph database is more accessible to third-party web services over the Internet, which thus opens the opportunity to connect to the rest of the world in the semantic format. The primary purpose of this pilot project is to evaluate the feasibility of converting registry objects in Research Graph to JSON-LD by accessing widely used vocabularies published at Schema.org. In this paper, we provide examples of publications, datasets and grants from international research institutions such as CERN INSPIREHEP, National Computational Infrastructure (NCI) in Australia, and Australian Research Council (ARC). Furthermore, we show how these Research Graph records are made semantically available as Linked Data through using Schema.org. The mapping between Research Graph schema and Schema.org is available on GitHub repository. We also discuss the potential need for an extension to Schema.org vocabulary for scholarly communication.

A Digital Repository for Physical Samples: Concepts, Solutions and Management

Physical samples are important resources for sample-based data reuse. They may be utilized in the reproduction of scientific findings, depending on their availability and accessibility. Although several solutions have been developed to curate and publish digital collections (e.g., publications and datasets), considerably less attention has been paid to providing access to physical samples, and linking them to data, reports, and other resources on the Internet. Some progress has been made to bring physical samples into the digital world; for example, through the web-identifier schemes, sample metadata standards and catalogues, and specimen digitization. Existing studies based on the above examples are either project or domain-specific. Also, a particular challenge exists in providing citable and resolvable identifiers for physical samples outside the context of an individual project or a sample data repository. Within the Commonwealth Scientific and Industrial Research Organisation (CSIRO), further work is needed in order to connect the various types of physical samples collected by different entities (individual researchers, projects and laboratories) to the Web, and enable their discovery. We address this need through the development a digital repository of physical samples. This paper presents technical and non-technical components of the repository. They were applied to unambiguously identify the various physical samples and to systematically provide continuous online access to their metadata and data.