Towards the Geo-spatial Querying of the Semantic Web with ONTOAST

Miron, Alina Dia; Gensel, Jérôme; Villanova-Oliver, Marlène; Martin, Hervé

doi:10.1007/978-3-540-76925-5_9

Cited by 9 publications

(11 citation statements)

References 8 publications

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“…While the use of Semantic Web technologies in driving mapping applications is becoming increasingly popular, a large body of the reported work, while valuable in its domain of interest, either focuses on the usability of the semantic of geo-spatial applications (Cloug et al 2011) (Becker and Bizer 2009), or predominantly focuses on geo-spatial problem solving aspects (Miron et al 2007) (Brodaric 2007). Research that is more related to our work investigates more explicitly the processes of exploiting the Semantic Web technology.…”

Section: Related Workmentioning

confidence: 99%

Investigating The Use Of Semantic Technologies In Spatial Mapping Applications

Osman¹,

Shires²,

Omitola³

et al. 2013

ECMS 2013 Proceedings Edited By: Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang

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Semantic Web Technologies are ideally suited to build context-aware information retrieval applications. However, the geospatial aspect of context awareness presents unique challenges such as the semantic modelling of geographical references for efficient handling of spatial queries, the reconciliation of the heterogeneity at the semantic and geo-representation levels, maintaining the quality of service and scalability of communicating, and the efficient rendering of the spatial queries' results. In this paper, we describe the modelling decisions taken to solve these challenges by analysing our implementation of an intelligent planning and recommendation tool that provides location-aware advice for a specific application domain. This paper contributes to the methodology of integrating heterogeneous geo-referenced data into semantic knowledgebases, and also proposes mechanisms for efficient spatial interrogation of the semantic knowledgebase and optimising the rendering of the dynamically retrieved context-relevant information on a web frontend.

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Section: Related Workmentioning

confidence: 99%

Investigating The Use Of Semantic Technologies In Spatial Mapping Applications

Osman¹,

Shires²,

Omitola³

et al. 2013

ECMS 2013 Proceedings Edited By: Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang

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show abstract

“…Once obtained, the results of such computations should be integrated back into the ontological space, becoming available for future reasoning activities. In (Miron et al, 2007b), we have proposed the use of a system called ONTOAST as an answer to the lack of specialized spatial and temporal inference engines defined on top of OWL or RDF(S) ontologies. ONTOAST is a spatio-temporal ontology modeling and query environment.…”

Section: Spatial and Temporal Reasoning For The Semantic Webmentioning

confidence: 99%

“…The temporal context is specified using an interval of the type (start_date, end_date) or (date, duration), together with a topological relation. The implicit topological relation is the inclusion, but all the topological temporal AML operators defined in (Miron et al, 2007b) can be used: before/after, starts/started-by, finishes/finishedby, during/contains, equals, meets/met-by, overlaps/overlapped-by. When a time interval is specified through a pair (date, duration), the temporal attributes describing tuples or objects are compared to the interval [date, date + duration].…”

Section: Temporal Contextmentioning

confidence: 99%

“…ONTOAST is built upon the spatio-temporal module AROM-ST. The interest of using ONTOAST lies in its predefined set of qualitative spatial and temporal associations (presented in details in (Miron et al, 2007b)). Those associations can be used in order to complete data on the modeled objects as well as to allow for a more flexible query formulation.…”

Section: Geospatial and Temporal Semantic Analysis Frameworkmentioning

confidence: 99%

“…ONTOAST (Miron et al, 2007b) is an OWL-DL compatible extension of the Object Based Representation System AROM (Page et al, 2001), a generic tool designed for knowledge modeling and inference. The originality of this system stands in its powerful and extensible typing system and in its Algebraic Modeling Language (Moisuc et al, 2005) used for expressing operational knowledge in a declarative way.…”

Section: Geospatial and Temporal Semantic Analysis Frameworkmentioning

confidence: 99%

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Semantic Analysis for the Geospatial Semantic Web

Miron

Gensel

Villanova-Oliver

2010

Advances in Knowledge Discovery and Management

Self Cite

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Abstract. Semantic analysis is a new search paradigm for the Semantic Web, which aims the automatic extraction of semantic associations existing between individuals described in RDF(S) graphs. In order to infer additional semantic associations and to increase the accuracy of the analysis, we propose here, to adapt semantic analysis for OWL-DL ontologies. We also show that by taking into account spatio-temporal information which is usually attached to resources, new and possibly interesting semantic associations can be discovered. Moreover, we propose to handle spatial and temporal contexts in order to limit the scope of the analysis to a given region of space and a given period of time, considered interesting from the user's point of view. For reasoning with spatial and temporal information and relations we use ONTOAST, a spatio-temporal representation and querying system, which is compatible with OWL-DL.

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