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Sensors 2015, 15(7), 17470-17482; doi:10.3390/s150717470

A Geospatial Semantic Enrichment and Query Service for Geotagged Photographs

1
School of Computing and Mathematics, University of Ulster, Coleraine BT370QB, UK
2
School of Computing and Information Engineering, University of Ulster, Coleraine BT521SA, UK
3
School of Computer Science and Informatics, De Montfort University, Leicester LE19BH, UK
4
IN2 Search Interfaces Development Ltd., 22 Forth Street, Edinburgh EH13LH, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Jesús Fontecha
Received: 7 May 2015 / Revised: 10 July 2015 / Accepted: 13 July 2015 / Published: 20 July 2015
View Full-Text   |   Download PDF [823 KB, uploaded 22 July 2015]   |  

Abstract

With the increasing abundance of technologies and smart devices, equipped with a multitude of sensors for sensing the environment around them, information creation and consumption has now become effortless. This, in particular, is the case for photographs with vast amounts being created and shared every day. For example, at the time of this writing, Instagram users upload 70 million photographs a day. Nevertheless, it still remains a challenge to discover the “right” information for the appropriate purpose. This paper describes an approach to create semantic geospatial metadata for photographs, which can facilitate photograph search and discovery. To achieve this we have developed and implemented a semantic geospatial data model by which a photograph can be enrich with geospatial metadata extracted from several geospatial data sources based on the raw low-level geo-metadata from a smartphone photograph. We present the details of our method and implementation for searching and querying the semantic geospatial metadata repository to enable a user or third party system to find the information they are looking for. View Full-Text
Keywords: geospatial; Semantic; media enrichment; ontology; photograph; API geospatial; Semantic; media enrichment; ontology; photograph; API
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ennis, A.; Nugent, C.; Morrow, P.; Chen, L.; Ioannidis, G.; Stan, A.; Rachev, P. A Geospatial Semantic Enrichment and Query Service for Geotagged Photographs. Sensors 2015, 15, 17470-17482.

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