A Rule‐Based Strategy for the Semantic Annotation of Geodata

Klien, Eva

doi:10.1111/j.1467-9671.2007.01054.x

Cited by 48 publications

(48 citation statements)

References 25 publications

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“…At the data entity level (Figure 5), complex knowledge extraction tools are needed to identify entities and the concepts that represent them, for example, to identify geographical features on a picture, to identify movement on a video, to parse text descriptions, etc. For example, Klien [54] proposed a rule-based strategy for semantic annotation of data, where the conditions for an object to be an instance of a concept are expressed as a rule (e.g., a river is a waterway whose width is larger than 10 meters). Once semantic annotations are established, the semantics of VGI applications and sensor data sets is readily usable by reasoning systems of the semantic layer.…”

Section: Semantic Annotationmentioning

confidence: 99%

Semantic Interoperability of Sensor Data with Volunteered Geographic Information: A Unified Model

Bakillah

Liang

Zipf

et al. 2013

IJGI

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Abstract:The increasing availability of sensor devices has resulted in important volumes of sensor data, which has raised the issue of making these data fully discoverable and interpretable by applications and end-users. The idea of OGC Sensor Web Enablement (SWE) has addressed this issue by proposing a set of standards to enable accessibility of sensor data over the Web. Similarly, there is a growing interest in volunteered geographic information (VGI). Considering that several researchers have highlighted the potential of this new type of information as a complement to existing, "traditional" data, it becomes important to develop frameworks to support the integration of VGI from several sources and with other types of data. In this paper, we make a first step in this direction by proposing a framework for the semantic interoperability of sensor data and VGI. After having performed an investigation of the types of VGI applications, we have developed a conceptual model of VGI aligned with relevant ISO standards for describing geospatial features. The purpose of this model is to support the generation of common descriptions for VGI applications, which will act as interfaces to higher-level services, such as discovery and reasoning services, in order to be exploited in conjunction with sensor data by client applications. This process is described through architecture for semantic interoperability of sensor data and VGI that we have developed and that we intend to use to set guidelines for future research on integration of VGI in sensor data cyberinfrastructures. We illustrate the

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Section: Semantic Annotationmentioning

confidence: 99%

Semantic Interoperability of Sensor Data with Volunteered Geographic Information: A Unified Model

Bakillah

Liang

Zipf

et al. 2013

IJGI

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“…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. Also, our method could be one step towards realizing the goal of using reasoners to query data sources through ontology interface as proposed in [1].…”

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%

“…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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“…Automating this process facilitates the transition to managed semantic representations (Grcar and Klien 2007). Klien (2007) presented a rule-based strategy for the semantic annotation of geographical data that combines Semantic Web and Geospatial Web Services technology. Klien and Lutz (2005) proposed an automatic method of semantically annotating geographic data based on spatial relationships, taking advantage of the specific characteristics of geographic information.…”

mentioning

confidence: 99%