The Location Index (LOC-I) project, established in 2018, created a methodology and data models framework providing for a consistent way to seamlessly integrate spatial data from distributed sources. The target was Australian spatial data "of national significance", meaning most - initially all - of the data considered was Australian Federal government data. Going forward, Loc-I is not limited to this sort of data, so other government data (States, Local) as well as non-government data may be included.
See the project website, http://www.ga.gov.au/locationindex, for more project information.
The technical implementation of Loc-I was based on Semantic Web principles allowing for datasets to be published as Linked Data independently by data holders - different government departments, companies etc. - and consumed with minimal effort required for integration.
The technical implementation relied on a Loc-I Ontology, the main Loc-I model, multiple Background Models, fundamental, standards, data models that the Loc-I Ontology depended on, and, for some datasets, Dataset Models of their content that spefialise the Loc-I Ontology.
Figure 1 below shows the original detailed architecture diagram used to explain Loc-I’s parts from 2018 - 2021. This supermodel document does not detail the technical implementation of Loc-I elements but does provide a formal, integrated, model for all the elements in that figure. The OWL ontology elements represented on the left are all included in this supermodel unchanged, however several additional background ontologies and profiles have been added to better integrate Loc-I datasets' models. These include the OGC LD API profile [OGCLDAPI] wich is used to ensure data meets, or to build out data to meet, requirements of the Open Geospatail Consortium’s OGC API - Features [OGCAPI] which is now used as the standard API for Loc-I datasets. That standard was not available when the original Loc-I project was started in 2018.
This Loc-I Supermodel Specification document formally defines the technical model implementation of Loc-I including all previously created models and relations as well as new models that have been added since the original Loc-I project, for example data models for new Loc-I datasets.