2023 | Geo-Spatial meets Linked Data: open source solutions for semantic spatial data exchange

Описание: FOSS4G 2023 Prizren

Presenter: Luís M. de Sousa



The Ontology discipline made its way into the Computer Science domain in the
1990s, filling a gap in the architecture aspect of a still infant engineering
domain. Its most visible impact happened around the industry consortium Object
Management Group (OMG), leading first to the Unified Modelling Language (UML)
and later to the Model Driven Architecture (MDA). MDA became the base
infrastructure of data architectures and exchange mechanisms specified by
institutions such as the Open Geo-spatial Consortium (OGC) or the European
Commission (through the INPIRE directive).

However, a parallel path has been treaded by the World Wide Web Consortium (W3C). First with the specification of the Resource Description Framework (RDF), a new paradigm for data encoding leveraged on the WWW, and later with the Web Ontology Language (OWL), a pragmatic approach to ontology encoding, building on RDF. This infrastructure developed by the W3C became known as the Semantic Web, and also as Linked Data, for the innovative paradigm through which it connects disparate data sources and data domains.

The OGC would eventually approach the semantic web, specifying GeoSPARQL in 2013, an ontology and query language for linked geo-spatial data. However, technologies supporting this new standard were slow in materialising.

More recently, the specification by the OGC of a new set of data standards based on the OpenAPI technology set out a clear path for the convergence of geo-spatial data with the Semantic Web. New software is emerging, opening an entirely new world to geo-spatial data provision, a clear step forwards in practically, usability and semantics.

This address starts by reviewing the core concepts of the Semantic Web and
then reviews state-of-the-art software for the management, publication
and exploration of linked geo-spatial data. This addressed is targeted at SDI
professionals and data scientists wishing to upgrade the semantics of the data they create and use.