<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.