16,874 research outputs found
A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web
Over the past decade, rapid advances in web technologies, coupled with
innovative models of spatial data collection and consumption, have generated a
robust growth in geo-referenced information, resulting in spatial information
overload. Increasing 'geographic intelligence' in traditional text-based
information retrieval has become a prominent approach to respond to this issue
and to fulfill users' spatial information needs. Numerous efforts in the
Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the
Linking Open Data initiative have converged in a constellation of open
knowledge bases, freely available online. In this article, we survey these open
knowledge bases, focusing on their geospatial dimension. Particular attention
is devoted to the crucial issue of the quality of geo-knowledge bases, as well
as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic
Network, is outlined as our contribution to this area. Research directions in
information integration and Geographic Information Retrieval (GIR) are then
reviewed, with a critical discussion of their current limitations and future
prospects
Distributed Holistic Clustering on Linked Data
Link discovery is an active field of research to support data integration in
the Web of Data. Due to the huge size and number of available data sources,
efficient and effective link discovery is a very challenging task. Common
pairwise link discovery approaches do not scale to many sources with very large
entity sets. We here propose a distributed holistic approach to link many data
sources based on a clustering of entities that represent the same real-world
object. Our clustering approach provides a compact and fused representation of
entities, and can identify errors in existing links as well as many new links.
We support a distributed execution of the clustering approach to achieve faster
execution times and scalability for large real-world data sets. We provide a
novel gold standard for multi-source clustering, and evaluate our methods with
respect to effectiveness and efficiency for large data sets from the geographic
and music domains
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
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
Neogeography: The Challenge of Channelling Large and Ill-Behaved Data Streams
Neogeography is the combination of user generated data and experiences with mapping technologies. In this article we present a research project to extract valuable structured information with a geographic component from unstructured user generated text in wikis, forums, or SMSes. The extracted information should be integrated together to form a collective knowledge about certain domain. This structured information can be used further to help users from the same domain who want to get information using simple question answering system. The project intends to help workers communities in developing countries to share their knowledge, providing a simple and cheap way to contribute and get benefit using the available communication technology
Spatio-textual indexing for geographical search on the web
Many web documents refer to specific geographic localities and many
people include geographic context in queries to web search engines. Standard
web search engines treat the geographical terms in the same way as other terms.
This can result in failure to find relevant documents that refer to the place of
interest using alternative related names, such as those of included or nearby
places. This can be overcome by associating text indexing with spatial indexing
methods that exploit geo-tagging procedures to categorise documents with
respect to geographic space. We describe three methods for spatio-textual
indexing based on multiple spatially indexed text indexes, attaching spatial
indexes to the document occurrences of a text index, and merging text index
access results with results of access to a spatial index of documents. These
schemes are compared experimentally with a conventional text index search
engine, using a collection of geo-tagged web documents, and are shown to be
able to compete in speed and storage performance with pure text indexing
Extending a geo-catalogue with matching capabilities
To achieve semantic interoperability, geo-spatial applications need to be equipped with tools able to understand user terminology that is typically different from the one enforced by standards. In this paper we summarize our experience in providing a semantic extension to the geo-catalogue of the Autonomous Province of Trento (PAT) in Italy. The semantic extension is based on the adoption of the S-Match semantic matching tool and on the use of a specifically designed faceted ontology codifying domain specific knowledge. We also briefly report our experience in the integration of the ontology with the geo-spatial ontology GeoWordNet
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