Interoperability and Integration: An Updated Approach to Linked Data Publication at the Dutch Land Registry

Abstract

Kadaster, the Dutch National Land Registry and Mapping Agency, has been actively publishing their base registries as linked (open) spatial data for several years. To date, a number of these base registers as well as a number of external datasets have been successfully published as linked data and are publicly available. Increasing demand for linked data products and the availability of new linked data technologies have highlighted the need for a new, innovative approach to linked data publication within the organisation in the interest of reducing the time and costs associated with said publication. The new approach to linked data publication is novel in both its approach to dataset modelling, transformation, and publication architecture. In modelling whole datasets, a clear distinction is made between the Information Model and the Knowledge Model to capture both the organisation-specific requirements and to support external, community standards in the publication process. The publication architecture consists of several steps where instance data are loaded from their source as GML and transformed using an Enhancer and published in the triple store. Both the modelling and publication architecture form part of Kadaster’s larger vision for the development of the Kadaster Knowledge Graph through the integration of the various linked datasets.

Geospatial Linked Data Proliferation in NMCAs: Systematic Literature Review

“…Contemporary Linked Open Data tooling is often unable to properly advertise datasets' usefulness to potential users, thereby hampering reuse (Folmer et al, 2019;A. Rowland et al, 2021;Rowland et al, 2022). The Data on the Web Best Practices give general guidelines for publishing data on the Web but no specific guidelines about spatial data (van den Brink et al, 2018).…”

“…Contemporary Linked Open Data tooling is often unable to properly advertise datasets' usefulness to potential users, thereby hampering reuse (Folmer et al, 2019;A. Rowland et al, 2021;Rowland et al, 2022). Over the last few years, Linked Open Data have seen a relatively slow adoption speed, partly due to the lack of sufficiently distinctive and functional browsing and viewing facilities.…”

Bringing Federated Semantic Queries to the GIS-Based Scenario

“…Other approaches aimed at a more profound integration by enabling spatial query processing within SPARQL [10,36,37] by implementing a Linked Data connector framework as a set of toolboxes for Esri's ArcGIS to allow the retrieval, integration, and analysis of Linked Data from within GIS [6], or by developing new standards or extensions for spatial and temporal reasoning and querying over Linked Data [38].…”