Inhaltszusammenfassung

Geodesists work in Industry 4.0 and Spatial Information Management by using cross linked machines, people and data. Yet, one of the most popular technologies for interlinking data - Semantic Web technologies - have been largely absent from the geodesy community, because of the slow development of standards, a mandatory non-trivial conversion between geospatial features and graph data, and a lack of commonly available GIS tools to achieve this. This is slowly changing due to an increased aware...Geodesists work in Industry 4.0 and Spatial Information Management by using cross linked machines, people and data. Yet, one of the most popular technologies for interlinking data - Semantic Web technologies - have been largely absent from the geodesy community, because of the slow development of standards, a mandatory non-trivial conversion between geospatial features and graph data, and a lack of commonly available GIS tools to achieve this. This is slowly changing due to an increased awareness of the advantages of Linked Data technology in the GIS community and an improvement of standards in the Semantic Web community. Hence, the importance of open source software, open geodata and open access increases. A fundamental requirement for data sharing is the use of standardised data models. In this paper we compare two different modelling approaches for Irish Ogham Stones as a best practice example for linked open data management: One approach uses Wikidata, and the other a custom ontology. While Wikidata offers direct integration into the Linked Open Data Cloud and needs less technological expertise, using a custom ontology enables the creation of best-fitting data models. Both approaches facilitate the use of new information sources for the geodesy community. We aim to demonstrate how Linked Open Geodata can be re-used and further enriched with information from other open sources such as spatial data from OpenStreetMap. For this purpose, we also present a QGIS plugin and a modified geospatial web service, as well as a geo-optimised linked data browser, as solutions for bridging the gap between geospatial features and Linked Open Data triples.» weiterlesen» einklappen

Autoren

Klassifikation

DFG Fachgebiet:
Informatik

DDC Sachgruppe:
Ingenieurwissenschaften