Building Geospatial Ontologies from Geographical Databases

Baglioni, Miriam; Masserotti, Maria Vittoria; Renso, Chiara; Spinsanti, Laura

doi:10.1007/978-3-540-76876-0_13

Cited by 32 publications

(18 citation statements)

References 8 publications

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“…Typically, these rules produce concepts and relationships from tables depending on the schema of the database, such as the structure of the tables and the features of the primary and foreign keys. When dealing with geodatabases, new rules have been defined (Baglioni et al. 2007) in order to manage direct and indirect locations and connect them with the geospatial ontology.…”

Section: Semantic Integration Of Geospatial Datamentioning

confidence: 99%

Automatic Representation of Geographical Data from a Semantic Point of View through a New Ontology and Classification Techniques

Fonseca

Llano

2011

Transactions in GIS

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Providing Geographical Information Systems with mechanisms for processing geo‐data based on their semantics may help to solve problems like heterogeneity. This is because GIS could process geo‐data focusing on their meaning and not on their syntax and/or structure. An important aspect for achieving these objectives is the establishment of an automatic means of correspondence between geo‐data and their conceptualization in Higher Levels Ontologies (HLO). In this article, a new type of Ontology is proposed (Data‐Representation Ontology (DRO)). This Ontology describes the semantic embedded in geo‐data, which cannot be represented in current types of Ontologies. Across this Ontology, heterogeneous geographical data can be integrated in the semantic space contributing positively to the development of solutions for the problems of interoperability between heterogeneous systems. Likewise, we propose a new method for the automatic generation of the DRO and its interrelationships with HLO, based on pattern classification techniques. The experiments show that once the DRO is generated, the classifier can classify all data correctly. Thus, these data are semantically enriched. Moreover, this article shows how the topological relationships can enrich the semantics in the generated Ontology and increase the effectiveness of spatial analysis.

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Section: Semantic Integration Of Geospatial Datamentioning

confidence: 99%

Automatic Representation of Geographical Data from a Semantic Point of View through a New Ontology and Classification Techniques

Fonseca

Llano

2011

Transactions in GIS

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“…Baglioni et. al [3] proposed a method on accessing spatial database through ontology layer by semi-automatically building an application ontology from a geographical database and then enrich it with domain ontology by finding correspondence between the classes and properties of the two ontologies. The enriched ontology is said to be used in assisting query answering though it is not clear how semantic queries are translated to spatial SQL to databases.…”

Section: Rdf-based Data Integrationmentioning

confidence: 99%

“…The enriched ontology is said to be used in assisting query answering though it is not clear how semantic queries are translated to spatial SQL to databases. Also related is a project for semi-automatically adding semantic annotations to geospatial data [23], which uses OWL to provide semantic annotation and uses Semantic Web Rule Language (SWRL) 3 to add additional properties between instances based on the existing ontology. More general discussion on developing geospatial ontologies can be found in the work of Arpinar et.…”

Section: Rdf-based Data Integrationmentioning

confidence: 99%

“…For example, some methods [3,10] generate useful ontologies from geospatial databases, which can be used as the application and/or domain ontologies for our interface. We do not use OWL as in [23] but it may be possible to include OWL ontologies with help of reasoning tools.…”

Section: Rdf-based Data Integrationmentioning

confidence: 99%

“…Thus, to efficiently support ontology-based reasoning on geospatial data, it is necessary to keep legacy data stored in geodatabases and other data files while providing an ontology-enabled interface to translate user requests into queries to legacy data stores. To this end, there are projects focused on extracting ontology definitions from database schemas [3] and annotating geospatial data with semantic annotations based on OWL and inference rules [23]. However, it is not clear how the extracted ontology information can help translate user requests into queries to legacy data sources.…”

Section: Introductionmentioning

confidence: 99%

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Ontology-Based Geospatial Data Query and Integration

Zhao

Zhang

Wei

et al. 2008

Geographic Information Science

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Abstract. Geospatial data sharing is an increasingly important subject as large amount of data is produced by a variety of sources, stored in incompatible formats, and accessible through different GIS applications. Past efforts to enable sharing have produced standardized data format such as GML and data access protocols such as Web Feature Service (WFS). While these standards help enabling client applications to gain access to heterogeneous data stored in different formats from diverse sources, the usability of the access is limited due to the lack of data semantics encoded in the WFS feature types. Past research has used ontology languages to describe the semantics of geospatial data but ontology-based queries cannot be applied directly to legacy data stored in databases or shapefiles, or to feature data in WFS services. This paper presents a method to enable ontology query on spatial data available from WFS services and on data stored in databases. We do not create ontology instances explicitly and thus avoid the problems of data replication. Instead, user queries are rewritten to WFS getFeature requests and SQL queries to database. The method also has the benefits of being able to utilize existing tools of databases, WFS, and GML while enabling query based on ontology semantics.

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Methodology and intermediate layer for the automatic creation of ontology instances stored in relational databases

2012

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SUMMARY In this paper, we introduce our solution for mapping local ontologies to relational and object‐oriented representations. This solution is part of the GeoNis framework for the interoperability of geo‐information systems applications in a local community environment. The GeoNis framework is based on a hybrid ontology approach for data integration. Therefore, a very important subject in our research on semantic data integration is the creation of mapping between a spatial information source and its local ontology. We developed the OWL2RDB mapping language to create an intermediate layer between a relational database and the OWL ontology. This intermediate layer contains rules (expressed in the OWL2RDB language) for mapping between the structural elements of a relational database and the concepts of OWL ontologies. We also present a system that uses the OWL2RDB intermediate layer to create classes that can handle ontology instances stored in relational databases. We have developed a prototype for a tool that uses this proposed approach for the automatic generation of translator/wrapper components in the GeoNis interoperability environment. Copyright © 2012 John Wiley & Sons, Ltd.

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Building Geospatial Ontologies from Geographical Databases

Cited by 32 publications

References 8 publications

Automatic Representation of Geographical Data from a Semantic Point of View through a New Ontology and Classification Techniques

Automatic Representation of Geographical Data from a Semantic Point of View through a New Ontology and Classification Techniques

Ontology-Based Geospatial Data Query and Integration

Methodology and intermediate layer for the automatic creation of ontology instances stored in relational databases

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