Exploring for the Future (EFTF) is a four-year (2016-20) geoscience data and information acquisition program that aims to better understand on a regional scale the potential mineral, energy and groundwater resources concealed under cover in northern Australia and parts of South Australia. Hydrogeochemical surveys utilise groundwater as a passive sampling medium to reveal the chemistry of the underlying geology including hidden mineralisation. These surveys also potentially provide input into regional baseline groundwater datasets that can inform environmental monitoring and decision making. Geoscience Australia, as part of the Australian Government’s EFTF program, undertook an extensive groundwater sampling survey in collaboration with the Northern Territory Geological Survey and the Geological Survey of Queensland. During the 2017, 2018 and 2019 dry season, 224 groundwater samples (including field duplicate samples) were collected from 203 pastoral and water supply bores in the Tennant Creek-Mt Isa EFTF focus area of the Northern Territory and Queensland. An additional 38 groundwater samples collected during the 2013 dry season in the Lake Woods region from 35 bores are included in this release as they originate from within the focus area. The area was targeted to evaluate its mineral potential with respect to iron oxide copper-gold, sediment-hosted lead-zinc-silver and Cu-Co, and/or lithium-boron-potash mineral systems, among others. The 2017-2019 surveys were conducted across 21 weeks of fieldwork and sampled groundwater for a comprehensive suite of hydrogeochemical parameters, including isotopes, analysed over subsequent months. The present data release includes information and atlas maps of: 1) sampling sites; 2) physicochemical parameters (EC, pH, Eh, DO and T) of groundwater measured in the field; 3) field measurements of total alkalinity (HCO3-), dissolved sulfide (S2-), and ferrous iron (Fe2+); 4) major cation and anion results; 5) trace element concentrations; 6) isotopic results of water (δ18O and δ2H), DIC (δ13C), dissolved sulfate (δ34S and δ18O), dissolved strontium (87Sr/86Sr), and dissolved lead (204Pb, 206Pb, 207Pb, and 208Pb) isotopes; 7) dissolved hydrocarbon VFAs, BTEX, and methane concentrations, as well as methane isotopes (δ13C and δ2H); and 8) atlas of hydrogeochemical maps representing the spatial distribution of these parameters. Pending analyses include: CFCs and SF6; tritium; Cu isotopes; and noble gas concentrations (Ar, Kr, Xe, Ne, and 4He) and 3He/4He ratio. This data release (current as of July 2021) is the second in a series of staged releases and interpretations from the Northern Australia Hydrogeochemical Survey. It augments and revises the first data release, which it therefore supersedes. Relevant data, information and images are available through the GA website (https://pid.geoscience.gov.au/dataset/ga/133388) and GA’s EFTF portal (https://portal.ga.gov.au/).

The UN Decade of Ocean Science for Sustainable Development (Ocean Decade) challenges the ocean research community to map and understand the changing ocean to inform and stimulate social and economic development, while conserving marine ecosystems. To achieve these objectives, the methodologies that generate data and information about the ocean need to interoperate with unprecedented depth and scale. For this, we must expand global participation in ocean science through a new and coherent approach to best practice development, supporting capacity development and sharing across a dramatically expanded range of communities. Here, we present perspectives on this issue gleaned from the ongoing development of the UNESCO Intergovernmental Oceanographic Commission (IOC) Ocean Best Practices System (OBPS). The OBPS is collaborating with individuals and programs around the world to transform the way ocean methodologies are managed, in strong alignment with the Outcomes envisioned by the Ocean Decade. However, significant challenges remain. These include the haphazard management of methodologies across their life cycle, the ambiguous endorsement of what is “best” and when/where, and the inconsistent access to best practices across disciplines and cultures. To help address these challenges, this Perspective recommends how we - as a global marine science community - can ensure our methodological know-how supports the Ocean Decade outcomes through: promoting convergence of methodologies into context-dependent best practices; incorporating contextualized best practices into Ocean Decade Actions; clarifying who endorses which method and why; creating a global network of complementary ocean practices systems; and ensuring broader consistency and flexibility in international capacity development. <b>Citation:</b> Pearlman J, Buttigieg PL, Bushnell M, Delgado C, Hermes J, Heslop E, Hörstmann C, Isensee K, Karstensen J, Lambert A, Lara-Lopez A, Muller-Karger F, Munoz Mas C, Pearlman F, Pissierssens P, Przeslawski R, Simpson P, van Stavel J and Venkatesan R (2021) Evolving and Sustaining Ocean Best Practices to Enable Interoperability in the UN Decade of Ocean Science for Sustainable Development. Front. Mar. Sci. 8:619685. doi: 10.3389/fmars.2021.619685

<p>The Isotopic Atlas of Australia is one of the fundamental datasets in Geoscience Australia (GA)’s Exploring for the Future program. It is underpinned by a nationwide coverage of high-quality U-Th-Pb radiometric dates, mostly determined by Sensitive High Resolution Ion Micro Probe (SHRIMP). For the past decade, GA and the international SHRIMP community have relied on SQUID 2.50 software to process isotopic data acquired by SHRIMP for U-Th-Pb geochronology. However, SQUID 2.50 is obsolete because of dependency on Excel 2003, which is unsupported by Microsoft and will not operate on Windows 10. As a result, GA collaborated with the Cyber Infrastructure Research and Development Laboratory for Earth Sciences (CIRDLES.org) at the College of Charleston (USA) to redeploy SQUID 2.50 algorithms in an open-source, platform-independent and freely available Java application (Squid3). Squid3 replicates (rather than seeking to enhance) SQUID 2.50 logic and arithmetic, with substantial improvements in flexibility and interactivity. In this paper, we review documentation detailing widely trusted but little-known SQUID 2.50 algorithms and provide an overview of Squid3, focusing on the implementation and improvement of SQUID 2.50 functionality. The beta version of Squid3 is capable of end-to-end U-Th-Pb data processing, from ingestion of raw SHRIMP .xml files, through finalised summary calculations, to reporting of data arrays suitable for visualisation via packages such as Isoplot, Topsoil and IsoplotR. In production, Squid3 will enable users to sever links with Excel 2003, while ensuring the sustainability, reliability and relevance of SHRIMP data. <p><b>Citation:</b> Bodorkos, S., Bowring, J.F., and Rayner, N.M., 2020. Squid3: Next-generation data processing software for Sensitive High Resolution Ion Micro Probe (SHRIMP). In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

<p>Airborne electromagnetic (AEM) data can be acquired cost-effectively, safely and efficiently over large swathes of land. Inversion of these data for subsurface electrical conductivity provides a regional geological framework for water resources management and minerals exploration down to depths of ~200 m, depending on the geology. However, for legacy reasons, it is not uncommon for multiple deterministic inversion models to exist, with differing details in the subsurface conductivity structure. This multiplicity presents a non-trivial problem for interpreters who wish to make geological sense of these models. In this article, we outline a Bayesian approach, in which various spatial locations were inverted in a probabilistic manner. The resulting probability of conductivity with depth was examined in conjunction with multiple existing deterministic inversion results. The deterministic inversion result that most closely followed the high-credibility regions of the Bayesian posterior probability was then selected for interpretation. Examining credibility with depth also allowed interpreters to examine the ability of the AEM data to resolve the subsurface conductivity structure and base geological interpretation on this knowledge of uncertainty. <p> <b>Citation:</b> Ray, A., Symington, N., Ley-Cooper, Y. and Brodie, R.C., 2020. A quantitative Bayesian approach for selecting a deterministic inversion model. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.