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It is recognised that nowadays, users interact with large amounts of data that exist in disparate forms, and are stored under different settings. Moreover, it is true that the amount of structured and un-structured data outside a single well organised data management system is expanding rapidly. To address the recent challenges of managing large am...
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... It is also the ISO 19125-1 standard (ISO 2004), which deals with the representation and manipulation of simple features (a simple feature is a feature with all its spatial attributes described piecewise by straight line or planar interpolation between sets of points). As mentioned in Koubarakis et al. (2012), geometries in WKT are restricted to 0-, 1-, and 2-dimensional geometric objects that exist in 2-, 3-, or 4-dimensional coordinate space (i.e. R 2 , R 3 , or R 4 ). ...
... ( Koubarakis et al. (2012) and Kyzirakos et al. (2012) further propose a new version of the data model stRDF (Koubarakis & Kyzirakos, 2010) as mentioned above. In the new version of stRDF, called stRDF i , they opt for a more practical solution to the problem of representing geospatial data and use the OGC standards WKT and GML instead of linear constraints. ...
... (2) stSPARQL i Kyzirakos et al., 2012) For querying the spatiotemporal RDF model stRDF i Kyzirakos et al., 2012) in Section 4.1, Koubarakis et al. (2012) and Kyzirakos et al. (2012) propose an extension of SPARQL (Koubarakis & Kyzirakos, 2010), called stSPARQL i . (Koubarakis & Kyzirakos, 2010) Topological relations (Cuiet al. 1993) Allen-13 interval relations (Allen, 1983) stSPARQL i Kyzirakos et al., 2012) SPARQL extension ...
Currently, a large amount of spatial and spatiotemporal RDF data has been shared and exchanged on the Internet and various applications. Resource Description Framework (RDF) is widely accepted for representing and processing data in different (including spatiotemporal) application domains. The effective management of spatial and spatiotemporal RDF data are becoming more and more important. A lot of work has been done to study how to represent, query, store, and manage spatial and spatiotemporal RDF data. In order to grasp and learn the main ideas and research results of spatial and spatiotemporal RDF data, in this paper, we provide a comprehensive overview of RDF for spatial and spatiotemporal data management. We summarize spatial and spatiotemporal RDF data management from several essential aspects such as representation, querying, storage, performance assessment, datasets, and management tools. In addition, the direction of future research and some comparisons and analysis are also discussed in depth.
... • Strabon RDF store: is a triple store, under construction by the TELEIOS research group 17 [106]. It is implementing the specifications of st-SPARQL. ...
... It also provides text areas for displaying the results of the asked questions. 106 6.7 Implementing the user interface and query plans is the user selections and the output is the state variable value, which helps the query processing in de-6.7 Implementing the user interface and query plans 107 termining which query plan will be executed. Algorithm 6.7.2 shows the pseudo code for the query planner, which specifies which query plan will be executed. ...
Semantic Web data sources such as DBpedia are a rich resource of structured representations of
knowledge about geographical features and provide potential data for computing the results of
Question Answering System queries that require geo-spatial computations. Retrieval from these
resources of all content that is relevant to a particular spatial query of, for example, containment,
proximity or crossing is not always straightforward as the geometry is usually confined to point
representations and there is considerable inconsistency in the way in which geographical features
are referenced to locations. In DBpedia, some geographical feature instances have point
coordinates, others have qualitative properties that provide explicit or implicit spatial relationships
between named places, and some have neither of these.
This thesis demonstrates that structured geo-spatial query, a form of question answering, on
DBpedia can be performed with a hybrid query method that exploits quantitative and qualitative
spatial properties in combination with a high quality reference geo-dataset that can help to support
a full range of geo-spatial query operators such as proximity, containment and crossing as
well as vague directional queries such as Find airports north of London?. A quantitative model
based on the spatial directional relations in DBpedia has been used to assist in query processing.
Evaluation experiments confirm the benefits of combining qualitative and quantitative methods
for containment queries and of employing high-quality spatial data, as opposed to DBpedia
points, as reference objects for proximity queries, particularly for linear features. The high
quality geo-data also enabled answering questions impossible to answer with Semantic Web resources
alone, such as finding geographic features within some distance from a region boundary.
The contributions were validated by a prototype geo-spatial query system that combined qualitative
and quantitative processing and included ranking answers for directional queries based on
models derived from DBpedia contributed data.
... Note that only strdf:union is an aggregate function in the SELECT clause; strdf:intersection performs a computation involving the result of the aggregation and the value of ?baGeom which is one of the variables determining the grouping according to which the aggregate computation is performed. More details of stRDF and stSPARQL are given in [11]. ...
We present Strabon, a new RDF store that supports the state of the art semantic geospatial query languages stSPARQL and GeoSPARQL. To illustrate the expressive power o�ered by these query languages and their implementation in Strabon, we concentrate on the new version of the data model stRDF and the query language stSPARQL that we have developed ourselves. Like GeoSPARQL, these new versions use OGC standards to represent geometries where the original versions used linear constraints.We study the performance of Strabon experimentally and show that it scales to very large data volumes and performs, most of the times, better than all other geospatial RDF stores it has been compared with.
... 4 The data model stRDF and the query language stSPARQL stRDF is an extension of the W3C standard RDF that allows the representation of geospatial data that changes over time [12,15]. stRDF is accompanied by stSPARQL, an extension of the query language SPARQL 1.1 for querying and updating stRDF data. ...
... stRDF is accompanied by stSPARQL, an extension of the query language SPARQL 1.1 for querying and updating stRDF data. stRDF and stSPARQL use OGC standards (Well-Known Text and Geography Markup Language) for the representation of temporal and geospatial data [15]. In TELEIOS, stRDF is used to represent satellite image metadata (e.g., time of acquisition, geographical coverage), knowledge extracted from satellite images (e.g., a certain image comprises semantic annotations) and auxiliary geospatial data sets encoded as linked data. ...
... The stRDF model and stSPARQL query language have been implemented in the system Strabon which is freely available as open source software 15 . Strabon extends the well-known open source RDF store Sesame 2.6.3 and uses PostGIS as the backend spatially-enabled DBMS. ...
Advances in remote sensing technologies have allowed us to send an ever-increasing number of satellites in orbit around Earth. As a result, satellite image archives have been constantly increasing in size in the last few years (now reaching petabyte sizes), and have become a valuable source of information for many science and application domains (environment, oceanography, geology, archaeology, security, etc.). TELEIOS is a recent European project that addresses the need for scalable access to petabytes of Earth Observation data and the discovery of knowledge that can be used in applications. To achieve this, TELEIOS builds on scientific databases, linked geospatial data, ontologies and techniques for discovering knowledge from satellite images and auxiliary data sets. In this paper we outline the vision of TELEIOS (now in its second year), and give details of its original contributions on knowledge discovery from satellite images and auxiliary datasets, ontologies, and linked geospatial data.
... stRDF is an extension of the W3C standard RDF that allows the representation of geospatial data that changes over time [3,5]. stRDF is accompanied by stSPARQL, an extension of the query language SPARQL 1.1 for querying and updating stRDF data. ...
... stRDF is accompanied by stSPARQL, an extension of the query language SPARQL 1.1 for querying and updating stRDF data. stRDF and stSPARQL use OGC standards (WKT and GML) for the representation of temporal and geospatial data [5,4]. stRDF and stSPARQL have been implemented in the system Strabon which is freely available as open source software 9 . ...
Advances in remote sensing technologies have enabled public and commercial organizations to send an ever-increasing number of satellites in orbit around Earth. As a result, Earth Observation (EO) data has been constantly increasing in volume in the last few years, and is currently reaching petabytes in many satellite archives. For example, the multi-mission data archive of the TELEIOS partner German Aerospace Center (DLR) is expected to reach 2PB next year, while ESA estimates that it will be archiving 20PB of data before the year 2020. As the volume of data in satellite archives has been increasing, so have the scientific and commercial applications of EO data. Nevertheless, it is estimated that up to 95% of the data present in existing archives has never been accessed, so the potential for increasing exploitation is very big.
... Thus, starting in SemsorGrid4Env and continuing in FP7 project TELEIOS, we developed a new version of stRDF which respects our initial design decisions (especially the decision to represent geometries using literals), but uses OGC standards for the representation of geospatial data. In addition, we developed a new version of stSPARQL which extends SPARQL 1.1 for querying stRDF data [43]. Our work on this new version of stSPARQL has commonalities with the recent OGC work on GeoSPARQL as we will see below 39 . ...
... In the new version of stRDF [43] we use OGC standards for the representation of geospatial data. The datatypes strdf:WKT and strdf:GML are introduced to represent geometries serialized using the OGC standards WKT and GML which were presented in Section 3.4. ...
The recent availability of geospatial information as linked open data has generated new interest in geospatial query processing and reasoning, a topic with a long tradition of research in the areas of databases and artificial intelligence. In this paper we survey recent ad-vances in this important research topic, concentrating on issues of data modeling and querying.
