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Reasoning with place information on the Linked Data Web

Abdelmoty, Alia and Almuzaini, Khalid 2016. Reasoning with place information on the Linked Data Web. Presented at: Second International Conference on Big Data, Small Data, Linked Data and Open Data (Alldata 2016), Lisbon, Portugal, 21 - 25 February 2016. ALLDATA 2016 : The Second International Conference on Big Data, Small Data, Linked Data and Open Data (includes KESA 20. pp. 48-53.

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Abstract

The Linked Data Web (LDW) is an evolution of the traditional Web from a global information space of linked documents to one where both documents and data are linked. A significant amount of geographic information about places are currently being published on this LDW. These are used to qualify the location of other types of datasets. This paper examines the limitations in the nature of location representation in some typical examples of these Resource Description Framework (RDF) resources, primarily resulting from the simplified geometric representation of location and the incomplete and random use of spatial relationships to link place information. The paper proposes a qualitative model of place location that enforces an ordered representation of relative spatial relationships between places. The model facilitates the application of qualitative spatial reasoning on places to extract a potentially large percentage of implicit links between place resources, thus allowing place information to be linked and to be explored more fully and more consistently than what is currently possible. The paper describes the model and presents experimental results demonstrating the effectiveness of the model on realistic examples of geospatial RDF resources.

Item Type: Conference or Workshop Item (Paper)
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: qualitative place models; spatial reasoning; geospatial web.
Additional Information: The author(s) of a manuscript agree that, if the manuscript is accepted for publication in IARIA conferences, the published article will be copyrighted to IARIA (exception made for authors who are government employees). This license allows IARIA to retain the copyright, which, as per the copyright details, also allows anyone to freely copy, distribute, and display the copyrighted work, and derivative works based upon it, under the condition that the publication is used unaltered and properly referenced. In the case of authors who are government employees, IARIA retains the right to unlimited distribution as well as the right to grant unlimited distribution.
ISBN: 978-1-61208-457-2
Related URLs:
Date of First Compliant Deposit: 17 April 2016
Date of Acceptance: 2 December 2015
Last Modified: 04 Jun 2017 09:01
URI: http://orca-mwe.cf.ac.uk/id/eprint/89333

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