6,154 research outputs found
GeomRDF: A Geodata Converter with a Fine-Grained Structured Representation of Geometry in the Web
In recent years, with the advent of the web of data, a growing number of
national mapping agencies tend to publish their geospatial data as Linked Data.
However, differences between traditional GIS data models and Linked Data model
can make the publication process more complicated. Besides, it may require, to
be done, the setting of several parameters and some expertise in the semantic
web technologies. In addition, the use of standards like GeoSPARQL (or ad hoc
predicates) is mandatory to perform spatial queries on published geospatial
data. In this paper, we present GeomRDF, a tool that helps users to convert
spatial data from traditional GIS formats to RDF model easily. It generates
geometries represented as GeoSPARQL WKT literal but also as structured
geometries that can be exploited by using only the RDF query language, SPARQL.
GeomRDF was implemented as a module in the RDF publication platform Datalift. A
validation of GeomRDF has been realized against the French administrative units
dataset (provided by IGN France).Comment: 12 pages, 2 figures, the 1st International Workshop on Geospatial
Linked Data (GeoLD 2014) - SEMANTiCS 201
UK utility data integration: overcoming schematic heterogeneity
In this paper we discuss syntactic, semantic and schematic issues which inhibit the integration of utility data in the UK. We then focus on the techniques employed within the VISTA project to overcome schematic heterogeneity. A Global
Schema based architecture is employed. Although automated approaches to Global Schema definition were attempted
the heterogeneities of the sector were too great. A manual approach to Global Schema definition was employed. The
techniques used to define and subsequently map source utility data models to this schema are discussed in detail. In order to ensure a coherent integrated model, sub and cross domain validation issues are then highlighted. Finally the proposed framework and data flow for schematic integration is introduced
Investigating the use of semantic technologies in spatial mapping applications
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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Bridging between sensor measurements and symbolic ontologies through conceptual spaces
The increasing availability of sensor data through a variety of sensor-driven devices raises the need to exploit the data observed by sensors with the help of formally specified knowledge representations, such as the ones provided by the Semantic Web. In order to facilitate such a Semantic Sensor Web, the challenge is to bridge between symbolic knowledge representations and the measured data collected by sensors. In particular, one needs to map a given set of arbitrary sensor data to a particular set of symbolic knowledge representations, e.g. ontology instances. This task is particularly challenging due to the potential infinite variety of possible sensor measurements. Conceptual Spaces (CS) provide a means to represent knowledge in geometrical vector spaces in order to enable computation of similarities between knowledge entities by means of distance metrics. We propose an ontology for CS which allows to refine symbolic concepts as CS and to ground instances to so-called prototypical members described by vectors. By computing similarities in terms of spatial distances between a given set of sensor measurements and a finite set of prototypical members, the most similar instance can be identified. In that, we provide a means to bridge between the real-world as observed by sensors and symbolic representations. We also propose an initial implementation utilizing our approach for measurement-based Semantic Web Service discovery
Geospatial information infrastructures
Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Geospatial information infrastructures (GIIs) provide the technological, semantic,organizationalandlegalstructurethatallowforthediscovery,sharing,and use of geospatial information (GI). In this chapter, we introduce the overall concept and surrounding notions such as geographic information systems (GIS) and spatial datainfrastructures(SDI).WeoutlinethehistoryofGIIsintermsoftheorganizational andtechnologicaldevelopmentsaswellasthecurrentstate-of-art,andreïŹectonsome of the central challenges and possible future trajectories. We focus on the tension betweenincreasedneedsforstandardizationandtheever-acceleratingtechnological changes. We conclude that GIIs evolved as a strong underpinning contribution to implementation of the Digital Earth vision. In the future, these infrastructures are challengedtobecomeïŹexibleandrobustenoughtoabsorbandembracetechnological transformationsandtheaccompanyingsocietalandorganizationalimplications.With this contribution, we present the reader a comprehensive overview of the ïŹeld and a solid basis for reïŹections about future developments
Towards automated knowledge-based mapping between individual conceptualisations to empower personalisation of Geospatial Semantic Web
Geospatial domain is characterised by vagueness, especially in the semantic disambiguation of the concepts in the domain, which makes defining universally accepted geo- ontology an onerous task. This is compounded by the lack of appropriate methods and techniques where the individual semantic conceptualisations can be captured and compared to each other. With multiple user conceptualisations, efforts towards a reliable Geospatial Semantic Web, therefore, require personalisation where user diversity can be incorporated. The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the real world and will empower personalisation algorithms for the Semantic Web. Intelligent information processing over the Semantic Web can be achieved if different conceptualisations can be integrated in a semantic environment and mismatches between different conceptualisations can be outlined. In this paper, a formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare models defined in OWL. The algorithms are illustrated in a geographical domain using concepts from the SPACE ontology developed as part of the SWEET suite of ontologies for the Semantic Web by NASA, and are evaluated by comparing test cases of possible user misconceptions
Multi-Paradigm Reasoning for Access to Heterogeneous GIS
Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn
the web into a geospatial web services enabled place. Mediation
architectures like VirGIS overcome syntactical and semantical heterogeneity
between several distributed sources. On mobile devices,
however, this kind of solution is not suitable, due to limitations,
mostly regarding bandwidth, computation power, and available storage
space. The aim of this paper is to present a solution for providing
powerful reasoning mechanisms accessible from mobile applications
and involving data from several heterogeneous sources.
By adapting contents to time and location, mobile web information
systems can not only increase the value and suitability of the
service itself, but can substantially reduce the amount of data delivered
to users. Because many problems pertain to infrastructures
and transportation in general and to way finding in particular, one
cornerstone of the architecture is higher level reasoning on graph
networks with the Multi-Paradigm Location Language MPLL. A
mediation architecture is used as a âgraph providerâ in order to
transfer the load of computation to the best suited component â
graph construction and transformation for example being heavy on
resources. Reasoning in general can be conducted either near the
âsourceâ or near the end user, depending on the specific use case.
The concepts underlying the proposal described in this paper are
illustrated by a typical and concrete scenario for web applications
An Approach to Publish Spatial Data on the Web: The GeoLinked Data Case
In this paper we report on an ongoing process aimed at publishing hydrographical data on the Web with a Spanish GeoLinked Data Use Case. Moreover, we discuss the process we followed, and propose methodological guidelines for all the activities involved within the process
The DIGMAP geo-temporal web gazetteer service
This paper presents the DIGMAP geo-temporal Web gazetteer service, a system providing access to names of places, historical periods, and associated geo-temporal information. Within the DIGMAP project, this gazetteer serves as the unified repository of geographic and temporal information, assisting in the recognition and disambiguation of geo-temporal expressions over text, as well as in resource searching and indexing. We describe the data integration methodology, the handling of temporal information and some of the applications that use the gazetteer. Initial evaluation results show that the proposed system can adequately support several tasks related to geo-temporal information extraction and retrieval
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