University of Twente Student Theses


Linked spatial data: Beyond the linked open data cloud

Adlan, Chaidir Arsyan (2018) Linked spatial data: Beyond the linked open data cloud.

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Abstract:The Linked Open Data Cloud (LOD Cloud) is the constellation of available interlinked open datasets which has become one of the biggest repositories on the web. An increasing number of spatial semantically annotated datasets provide a huge potential source of knowledge for data enrichment in a spatial context.Yet, there is lack of information about the structure of the spatial datasets in the LOD Cloud which can discourage the integration efforts. In addition, most of the existing studies of link discovery have yet to exploit spatial information richness (topology and geometry). Thus, a structured way to assess spatial datasets and to integrate linked spatial data is required. This study aims to evaluate the LOD Cloud by assessing the data structure and the representation of linked spatial data, in order to support exploration and integration purposes. To achievethis objective, this study proposes: (i) a workflow for analyzinglinked spatial dataresourcesin the LOD Cloud, which consists of the identification of the linked spatial data sources, strategies for dataset retrieval, pipeline design for data processing, and linked data quality principles and metrics analysis;(ii) a review of linked data visualization systems, which includes an assessment of the current LOD Cloud Diagram based on expert opinion with respect to key requirements for visual representationandanalytics for linked data consumption; and(iii) a workflow for linked spatial data integration.The main contribution of this thesis is the provision of case studiesof integrating various spatial data sources. We presented two case studies, geometry-based integration using the spatial extension of Silk Link Discovery, and toponym-based integration using Similarity Measure. The datasets of Basisregistratie Topografie(BRT) Kadaster, Natura2000, and Geonames were used for the data integration. The results of the studyinclude: (i) astructured way to consume and extract spatial information from linked dataresources. In this thesis, we proposed one metric to assess linked spatial data, namelythe existence of geospatial ontology –vocabulary in the linked dataresources;(ii) identification of suitable visualization element for exploration and discovery, especially for spatial data. The top-level relationship (overview) visualization is potentially facilitating an effective datasets discovery and also able to expose the spatial content and relationship in a sensible way. This study discovered that the linkset concept in the level of the dataset, subset, and distribution could be used as basis information for overview visualization; and finally, (iii) findings of spatial components (geometry and toponym) that can be used as important “hook” for integrating different datasets. The commonlyused geospatial ontology and vocabulary also enable semantic interoperability to support data integration.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Geoinformation Science and Earth Observation MSc (75014)
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