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IJGI
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Geospatial Semantics and Semantic Web
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Geospatial Semantics and Semantic Web

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (30 September 2016) | Viewed by 26071

Special Issue Editors

Dr. E. Lynn Usery

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Guest Editor
Center of Excellence for Geospatial Information Science, U.S. Geological Survey, 1400 Independence Road, Rolla, MO 65401-2502, USA
Interests: theoretical cartography and geographic information science; geospatial semantics and ontology; CyberGIS; map projections; spatial data models; and data integration
Dr. Dalia Varanka

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Guest Editor
U.S. Geological Survey, 1400 Independence Road, Rolla, MO 65401, USA
Interests: GeoSpatial Semantics

Special Issue Information

Dear Colleagues,

Geospatial semantics and ontologies offer significant potential for enhanced search and query of geographic information. The development of the Semantic Web, Linked Open Data, and associated ontology and semantic tools provide opportunities for advancing research in geospatial information and geomatics. Research and development of ontologies and semantics in association with many recent advancements in geographic information systems (GIS), mobile mapping, volunteered geographic information (VGI), remote sensing, and spatial analysis are expanding the frontiers of geographic information science (GIScience). Semantics and ontologies are being developed and used in many traditional GIS application areas. The semantics necessary for data integration often require development of complete ontologies at the task level that relate to upper-level domain ontologies.
In this Special Issue we want to include original, unpublished research affecting geospatial semantics and ontologies. Specific topics of interest include but are not limited to geospatial ontologies, ontology-driven gazetteers, geospatial semantics, ontologies and semantics for geospatial data, especially topography, including terrain, hydrography, land cover, geographic names, transportation, and orthographic images. Other investigation topics include:

  • Spatial reasoning
  • Cartography and Visualization for Geospatial Semantics
  • Natural Language Interfaces
  • Linked Open Geospatial Data
  • Semantic Sensor Networks
  • Geospatial Ontology Patterns
  • Mobile Deployment of Semantic Technology
  • Intelligent Information Exploration and Query Processing
  • Ontology Matching and Semantic Interoperability
  • Semantics of Scale
  • Semantic Standards

Dr. Dalia Varanka
Dr. E. Lynn Usery
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Geospatial semantics
  • Domain ontology
  • Task ontology
  • Spatial ontology
  • Semantic Web
  • Resource Description Framework (RDF)
  • SPARQL/GeoSPARQL
  • Geospatial Semantic Web
  • Web Ontology Language (OWL)
  • Upper level ontologies

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Published Papers (4 papers)

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Research

1304 KiB  
Article
An Automatic Matcher and Linker for Transportation Datasets
by Ali Masri, Karine Zeitouni, Zoubida Kedad and Bertrand Leroy
ISPRS Int. J. Geo-Inf. 2017, 6(1), 29; https://doi.org/10.3390/ijgi6010029 - 22 Jan 2017
Cited by 3 | Viewed by 5544
Abstract
Multimodality requires the integration of heterogeneous transportation data to construct a broad view of the transportation network. Many new transportation services are emerging while being isolated from previously-existing networks. This leads them to publish their data sources to the web, according to linked [...] Read more.
Multimodality requires the integration of heterogeneous transportation data to construct a broad view of the transportation network. Many new transportation services are emerging while being isolated from previously-existing networks. This leads them to publish their data sources to the web, according to linked data principles, in order to gain visibility. Our interest is to use these data to construct an extended transportation network that links these new services to existing ones. The main problems we tackle in this article fall in the categories of automatic schema matching and data interlinking. We propose an approach that uses web services as mediators to help in automatically detecting geospatial properties and mapping them between two different schemas. On the other hand, we propose a new interlinking approach that enables the user to define rich semantic links between datasets in a flexible and customizable way. Full article
(This article belongs to the Special Issue Geospatial Semantics and Semantic Web)
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1552 KiB  
Article
Towards a Common Framework for the Identification of Landforms on Terrain Models
by Eric Guilbert and Bernard Moulin
ISPRS Int. J. Geo-Inf. 2017, 6(1), 12; https://doi.org/10.3390/ijgi6010012 - 12 Jan 2017
Cited by 21 | Viewed by 7788
Abstract
A landform is a physical feature of the terrain with its own recognisable shape. Its definition is often qualitative and inherently vague. Hence, landforms are difficult to formalise in a logical model that can be implemented. We propose for that purpose a framework [...] Read more.
A landform is a physical feature of the terrain with its own recognisable shape. Its definition is often qualitative and inherently vague. Hence, landforms are difficult to formalise in a logical model that can be implemented. We propose for that purpose a framework where these qualitative and vague definitions are transformed successively during different phases to yield an implementable data structure. Our main consideration is that landforms are characterised by salient elements as perceived by users. Hence, a common prototype based on an object-oriented approach is defined that shall apply to all landforms. This framework shall facilitate the definition of conceptual models for other landforms and relies on the use of ontology design patterns to express common elements and structures. The model is illustrated on examples from the literature, showing that existing works undertaken separately can be developed under a common framework. Full article
(This article belongs to the Special Issue Geospatial Semantics and Semantic Web)
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4046 KiB  
Article
An Integrated Software Framework to Support Semantic Modeling and Reasoning of Spatiotemporal Change of Geographical Objects: A Use Case of Land Use and Land Cover Change Study
by Wenwen Li, Xiran Zhou and Sheng Wu
ISPRS Int. J. Geo-Inf. 2016, 5(10), 179; https://doi.org/10.3390/ijgi5100179 - 30 Sep 2016
Cited by 12 | Viewed by 6164
Abstract
Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC) over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in effective organization, representation [...] Read more.
Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC) over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in effective organization, representation and modeling of such information. This study proposes and implements an integrated computational framework to support the modeling, semantic and spatial reasoning of change information with regard to space, time and topology. We first proposed a conceptual model to formally represent the spatiotemporal variation of change data, which is essential knowledge to support various environmental and social studies, such as deforestation and urbanization studies. Then, a spatial ontology was created to encode these semantic spatiotemporal data in a machine-understandable format. Based on the knowledge defined in the ontology and related reasoning rules, a semantic platform was developed to support the semantic query and change trajectory reasoning of areas with LULCC. This semantic platform is innovative, as it integrates semantic and spatial reasoning into a coherent computational and operational software framework to support automated semantic analysis of time series data that can go beyond LULC datasets. In addition, this system scales well as the amount of data increases, validated by a number of experimental results. This work contributes significantly to both the geospatial Semantic Web and GIScience communities in terms of the establishment of the (web-based) semantic platform for collaborative question answering and decision-making. Full article
(This article belongs to the Special Issue Geospatial Semantics and Semantic Web)
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2369 KiB  
Article
Geospatial Information Categories Mapping in a Cross-lingual Environment: A Case Study of “Surface Water” Categories in Chinese and American Topographic Maps
by Xi Kuai, Lin Li, Heng Luo, Shen Hang, Zhijun Zhang and Yu Liu
ISPRS Int. J. Geo-Inf. 2016, 5(6), 90; https://doi.org/10.3390/ijgi5060090 - 14 Jun 2016
Cited by 11 | Viewed by 5411
Abstract
The need for integrating geospatial information (GI) data from various heterogeneous sources has seen increased importance for geographic information system (GIS) interoperability. Using domain ontologies to clarify and integrate the semantics of data is considered as a crucial step for successful semantic integration [...] Read more.
The need for integrating geospatial information (GI) data from various heterogeneous sources has seen increased importance for geographic information system (GIS) interoperability. Using domain ontologies to clarify and integrate the semantics of data is considered as a crucial step for successful semantic integration in the GI domain. Nevertheless, mechanisms are still needed to facilitate semantic mapping between GI ontologies described in different natural languages. This research establishes a formal ontology model for cross-lingual geospatial information ontology mapping. By first extracting semantic primitives from a free-text definition of categories in two GI classification standards with different natural languages, an ontology-driven approach is used, and a formal ontology model is established to formally represent these semantic primitives into semantic statements, in which the spatial-related properties and relations are considered as crucial statements for the representation and identification of the semantics of the GI categories. Then, an algorithm is proposed to compare these semantic statements in a cross-lingual environment. We further design a similarity calculation algorithm based on the proposed formal ontology model to distance the semantic similarities and identify the mapping relationships between categories. In particular, we work with two GI classification standards for Chinese and American topographic maps. The experimental results demonstrate the feasibility and reliability of the proposed model for cross-lingual geospatial information ontology mapping. Full article
(This article belongs to the Special Issue Geospatial Semantics and Semantic Web)
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