Spatial data fusion in Spatial Data Infrastructures using Linked Data

Wiemann, Stefan; Bernard, Lars

doi:10.1080/13658816.2015.1084420

Cited by 48 publications

(36 citation statements)

References 41 publications

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“…Such knowledge bases have the potential to lead online geospatial data analysis to a finer scale. For example, a few recent studies have already begun to fuse spatial features in spatial data infrastructures using both W3C and OGC standards (Wiemann and Bernard, 2016;Wiemann, 2017). Given the various subjects and heavy volume of geoscience data and the joint efforts between OGC and W3C, there could be various methods and technologies to add semantics into datasets and data services (cf.…”

Section: Discussionmentioning

confidence: 99%

Linked Geoscience Data in practice: where W3C standards meet domain knowledge, data visualization and OGC standards

2017

Earth Sci Inform

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Abstract:The geoscience community is now facing both the challenge and the opportunity caused by the vast amount of datasets that can be made available on the Web. An efficient "data environment" on the Web has the potential to enable geoscientists to conduct their research in ways that never existed before. Standards developed by the Open Geospatial Consortium have already been used widely to build data services among different subjects in geosciences. In recent years, the Linked Open Data approach initiated by the World Wide Web Consortium has received increasing attention. In this paper, the author presents a pilot study that uses a domain specific knowledge base and data visualization techniques to leverage the functionality of geoscience data services in the Web of Data. The study focuses on the topic of the geologic time scale. Detailed works such as semantic modeling and encoding, multilingual vocabularies, exploratory data visualization, web map service and processing, and the query of linked data are introduced through real-world datasets. This study faces a broad perspective of the Linked Geoscience Data and leverages the functionalities of existing standards into a new level for geoscience applications.

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Section: Discussionmentioning

confidence: 99%

Linked Geoscience Data in practice: where W3C standards meet domain knowledge, data visualization and OGC standards

2017

Earth Sci Inform

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“…In addition, flexibility and interoperability are key factors in such data integration. Hence, the use of standards is a basic requirement (Wiemann & Bernard, ). In this sense, progress on Linked Data, ontologies, and geospatial semantics (Kuhn, ) are considered in this study case, due to the fact that they provide the decisive glue between models, data, and users (Janowicz & Hitzler, ).…”

Section: A Case Study With Biodiversity Data Sourcesmentioning

confidence: 99%

“…Although SDIs and Linked Data are quite different in respect of their architectures, workflows, and applied standards, they can be regarded as complementary (Wiemann & Bernard, ). Therefore, this combination (SDI and Semantic Web) can make the data easy to find and easy to access for non‐specialist users, since geospatial data becomes integrated within the wider Web of Data.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, this combination (SDI and Semantic Web) can make the data easy to find and easy to access for non‐specialist users, since geospatial data becomes integrated within the wider Web of Data. Under this approach, different work has appeared combining SDI Web services and Linked Data, especially for bringing to SDIs the integration and reasoning capabilities of the Semantic Web (Lutz & Klien, ; Roman & Klien, ; Janowicz et al, ; Yue, Gong, Di, He, & Wei, ; Hietanen, Lehto, & Latvala, ; Wiemann & Bernard, ).…”

Section: Introductionmentioning

confidence: 99%

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A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data

Vilches‐Blázquez

Saavedra

2018

Transactions in GIS

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Diverse studies have shown that about 80% of all available data are related to a spatial location. Most of these geospatial data are available as structured and semi-structured datasets, and often use distinct data models, are encoded using ad-hoc vocabularies, and sometimes are being published in non-standard formats. Hence, these data are isolated within silos and cannot be shared and integrated across organizations and communities. Spatial Data Infrastructures (SDIs) have emerged and contributed to significantly enhance data discovery and accessibility based on OGC (Open Geospatial Consortium) Web services. However, finding, accessing, and using data disseminated through SDIs are still difficult for non-expert users.Overcoming the current geospatial data challenges involves adopting the best practices to expose, share, and integrate data on the Web, that is, Linked Data. In this article, we have developed a framework for generating, enriching, and exploiting geospatial Linked Data from multiple and heterogeneous geospatial data sources. This proposal allows connecting two interoperability universes (SDIs, more specifically Web Feature Services, WFS, and Semantic Web technologies), which is evaluated through a study case in the (geo)biodiversity domain. | 23VILCHES-BLÁZQUEZ and SAAVEDRA

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“…These linkages are widely used for updating, maintaining, and integrating spatial data (Ruiz, Ariza, Urena, & Blazquez, ). In recent years, a large amount of geographic data was voluntarily collected by citizens (Goodchild, ; Wiemann & Bernard, ). To feasibly use these data, object matching plays an important role in their quality assessment (Koukoletsos, Haklay, & Ellul, ; Neis & Zielstra, ; Senaratne, Mobasheri, Ali, Capineri, & Haklay, ).…”

Section: Introductionmentioning

confidence: 99%

M:N Object matching on multiscale datasets based on MBR combinatorial optimization algorithm and spatial district

Liu

Zhu

et al. 2018

Transactions in GIS

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Object matching is critical for updating, maintaining, integrating, and quality assessing spatial data. However, matching data are often obtained from different sources and have problems of positional discrepancy and different levels of detail. To resolve these problems, this article presents a multiscale polygonal object-matching approach, called the minimum bounding rectangle combinatorial optimization (MBRCO) with spatial district (SD). This method starts with the MBRCO algorithm and its enhancement using the SD to find corresponding MBRs of one-to-one, one-to-many, and many-to-many matching pairs. Then, it aligns the MBRs of the matching pairs to identify objectmatching pairs, which are evaluated using a matching criterion to find geometrically corresponding objects. Our approach was experimentally validated using two topographical datasets at 1:2k and 1:10k. The proposed approach outperforms the common two-way area overlap method and another method based on the contextual information and relaxation labeling algorithm. The proposed method achieved accurate aggregation of the many-tomany matching pairs under the positional discrepancy scenario.

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Spatial data fusion in Spatial Data Infrastructures using Linked Data

Cited by 48 publications

References 41 publications

Linked Geoscience Data in practice: where W3C standards meet domain knowledge, data visualization and OGC standards

Linked Geoscience Data in practice: where W3C standards meet domain knowledge, data visualization and OGC standards

A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data

M:N Object matching on multiscale datasets based on MBR combinatorial optimization algorithm and spatial district

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