<div>GeoInsight was an 18-month pilot project developed in the latter part of Geoscience Australia’s Exploring for the Future Program (2016–2024). The aim of this pilot was to develop a new approach to communicating geological information to non-technical audiences, that is, non-geoscience professionals. The pilot was developed using a human-centred design approach in which user needs were forefront considerations. Interviews and testing found that users wanted a simple and fast, plain-language experience which provided basic information and provided pathways for further research. GeoInsight’s vision is to be an accessible experience that curates information and data from across the Geoscience Australia ecosystem, helping users make decisions and refine their research approach, quickly and confidently.</div><div><br></div><div>Geoscience Australia hosts a wealth of geoscientific data, and the quantity of data available in the geosciences is expanding rapidly. This requires newly developed applications such as the GeoInsight pilot to be adaptable and malleable to changes and updates within this data. As such, utilising the existing Oracle databases, web service publication and platform development workflows currently employed within Geoscience Australia (GA) were optimal choices for data delivery for the GeoInsight pilot.&nbsp;This record is intended to give an overview of the how and why of the technical infrastructure of this project. It aims to summarise how the underlying databases were used for both existing and new data, as well as development of web services to supply the data to the pilot application.&nbsp;</div>

<div>Geoscience Australia's geoscientific relational databases use look-up tables to describe the data stored within. These look-ups contain, but are not limited to, information about boreholes, field geology, inorganic and organic geochemistry, hydrochemistry, geophysics, rock properties, samples and other general geological terms. These terms have then been compiled into a vocabulary of terms for publication via GA's vocabulary service. Within this vocabulary, GA references where sourced terms are published in external vocabularies with a source vocabulary URI (Uniform Resource Identifier). </div><div><br></div><div>All vocabularies, collections of concepts within vocabularies and individual concepts are identified with URI persistent identifiers of the form:</div><div>http://pid.geoscience.gov.au/def/voc/ga/{VOCABULARY-KEY}/{COLLECTION-OR-CONCEPT-NAME}</div>

Seabed morphology maps and data are critical for knowledge-building and best practice management of marine environments. To facilitate objective and repeatable production of these maps, we have developed a number of semi-automated, rule-based GIS tools (Geoscience Australia’s Semi-automated Morphological Mapping Tools (GA-SaMMT)) to operationalise the mapping of a common set of bathymetric high and bathymetric low seabed Morphological Features. The tools have a graphical user interface and were developed using Python scripts under the widely-used proprietary ArcGIS Pro platform. The utility of these tools was tested across nine case study areas that represent a diverse range of complex bathymetric and physiographic settings. Overall, the mapping results are found to be more consistent than manual mapping and allow for capture of greater detail across a range of spatial scales. The mapping results demonstrate a number of advantages of GA-SaMMT, including: 1) requirement of only a bathymetry grid as sole data input; 2) flexibility to apply domain knowledge to user-defined tool parameters or to use default parameter settings; 3) repeatability and consistency in the mapping outputs when using a consistent set of tool parameters (user defined or default); 4) high-degree of objectivity; and 5) efficiency in mapping a large number (thousands) of seabed morphology features in a single dataset. In addition, GA-SaMMT generates 34 and 46 metrics to comprehensively quantify the characteristics of individual seabed bathymetric high and low features, respectively. Our results indicate that attribute metrics are invaluable in the interpretation and modelling of mapped Morphology Features and provide insights into their formative processes and habitat potential for marine communities. Appeared in Front. Mar. Sci., 28 August 2023, Sec. Ocean Observation, Volume 10.