Bringing Federated Semantic Queries to the GIS-Based Scenario

Oswaldo Páez,Luis M Vilches-Blázquez

doi:10.3390/ijgi11020086

Oswaldo Páez, Luis M Vilches-Blázquez

Open Access

https://doi.org/10.3390/ijgi11020086

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Abstract

Geospatial data is increasingly being made available on the Web as knowledge graphs using Linked Data principles. This entails adopting the best practices for publishing, retrieving, and using data, providing relevant initiatives that play a prominent role in the Web of Data. Despite the appropriate progress related to the amount of geospatial data available, knowledge graphs still face significant limitations in the GIScience community since their use, consumption, and exploitation are scarce, especially considering that just a few developments retrieve and consume geospatial knowledge graphs from within GIS. To overcome these limitations and address some critical challenges of GIScience, standards and specific best practices for publishing, retrieving, and using geospatial data on the Web have appeared. Nevertheless, there are few developments and experiences that support the possibility of expressing queries across diverse knowledge graphs to retrieve and process geospatial data from different and distributed sources. In this scenario, we present an approach to request, retrieve, and consume (geospatial) knowledge graphs available at diverse and distributed platforms, prototypically implemented on Apache Marmotta, supporting SPARQL 1.1 and GeoSPARQL standards. Moreover, our approach enables the consumption of geospatial knowledge graphs through a lightweight web application or QGIS. The potential of this work is shown with two examples that use GeoSPARQL-based knowledge graphs.

Highlights

Geospatial data is increasingly being made available on the Web [1] in the form of knowledge graphs in the Semantic Web, often using Linked Data principles [2]
This work contributes to filling a gap and makes possible the exploitation of GeoSPARQL-based resources in a distributed environment through federated practices, helping the GIScience community to use the richness of the Web of Data
The web application was developed with Node.js and Leaflet, and it provides end-users a SPARQL Endpoint connected to Apache Marmotta for writing federated GeoSPARQL queries

Summary

Introduction

Geospatial data is increasingly being made available on the Web [1] in the form of knowledge graphs in the Semantic Web, often using Linked Data principles [2]. The transformation and publication of geospatial data as knowledge graphs were pioneered by initiatives such as GeoNames (http://www.geonames.org/ontology/documentation.html (accessed on 23 November 2021)), OpenStreetMap [4], and Ordnance Survey [5] After these initiatives, many geospatial datasets have been published in the Web of Data Google rediscovered and spread a new vision of this concept when it introduced its notion about a new web search strategy in 2012 (https://googleblog.blogspot.com/20 12/05/introducing-knowledge-graph-things-not.html (accessed on 23 November 2021)) It involved changing from pure text processing to a more symbolic representation of knowledge, expressed in the following way:. “The Knowledge Graph enables you to search for things, people or places that Google knows about landmarks, celebrities, cities, sports teams, buildings, geographical features, movies, celestial objects, works of art and more and instantly get information that is relevant to your query. The graphs present resource descriptions, for instance: metadata about social networks, digital artifacts, personal information, etc., and supply a mechanism of integration over heterogeneous information sources; (2) RDF datasets are employed to make RDF graph collections and generate a default graph and zero or more named graphs

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