This the top-level collection record for all of Geoscience Australia's public vocabularies. The vocabularies are all formulated using the SKOS (Simple Knowledge Organization System) information model and delivered both as machine-readable Resource Description Framework (RDF) data and also as HTML web pages. Each vocabulary is delivered individually as RDF & HTML data and all vocabularies are linked to from both GA's vocabularies index static web page and also from the Australian National Data Service (ANDS)'s Research Vocabularies Australia (RVA) portal. All vocabularies, collections of concepts within vocabularies and individual concepts are identified with URI persistent identifiers of the form: http://pid.geoscience.gov.au/def/voc/ga/{VOCABULARY-KEY}/{COLLECTION-OR-CONCEPT-NAME} This means that you can access all the information about a vocabulary, a collection or a concept directly by entering that URI into your web browser.

A prototype Python, utility called ncskosdump, which wraps the ncdump netCDF reading tool and adds a series of options for the retrieval and display of Linked Data that the tool is able to extract from a netCDF file, including links to vocabulary terms. The tool is presented in a code repository using the Git distributed version control system.

A Linked Data API, using Python Flask which is an HTTP API framework, used to deliver representations of GA's aerial Surveys online as Linked Data. The API reads data from another HTTP API: the ARGUS XML API. The ARGUS XML API is generated by Oracle software and delivers XML representations of Survey objects stored in the ARGUS database. The online endpoints for the ARGUS XML API as accessed by this Surveys API are given in a config file within this API's code. Details about how to use this API are given within the main README file of this API's code repository (README.md).

This Agreements ontology is designed to model 'agreements' which are social contracts that include: licenses, laws, contracts, Memoranda of Understanding, standards and definitional metadata. Its purpose is to support data sharing by making explicit the relationships between agreements and data and agreements and Agents (people and organisations). Eventually it will also help with the interplay between different classes of agreements. We think of this ontology as a 'middle' ontology, that is one which specializes well-known, abstract, upper ontologies and is able to be used fairly widely but is expected to be used particular contexts in conjunction with detailed, domain-specific, lower ontologies. We have tried to rely on: existing agent, data manipulation, metadata and licence ontologies where possible. As such we specialise the ORG and FOAF ontologies; the PROV ontology; the Dublin Core Terms RDF schema & DCAT ontology; and the ODRS vocabulary & Creative Commons RDF data models for those areas, respectively