Scipediacontent: Scipediacontent moved page Draft Content 645998152 to Mobasheri 2017a

2021-01-28T20:44:20Z

Scipediacontent moved page Draft Content 645998152 to Mobasheri 2017a

Scipediacontent: Created page with " == Abstract == Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available within the emerging “Big Data”..."

2021-01-28T20:44:15Z

Created page with " == Abstract == Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available within the emerging “Big Data”..."

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== Abstract ==

Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available within the emerging “Big Data” era. Users are expecting that the availability of massive datasets will create more opportunities to uncover hidden information and answer more complex queries. This is especially the case with routing and navigation services where the ability to retrieve points of interest and landmarks make the routing service personalized, precise, and relevant. In this paper, we propose a new geospatial information approach that enables the retrieval of implicit information, i.e., geospatial entities that do not exist explicitly in the available source. We present an information broker that uses a rule-based spatial reasoning algorithm to detect topological relations. The information broker is embedded into a framework where annotations and mappings between OpenStreetMap data attributes and external resources, such as taxonomies, support the enrichment of queries to improve the ability of the system to retrieve information. Our method is tested with two case studies that leads to enriching the completeness of OpenStreetMap data with footway crossing points-of-interests as well as building entrances for routing and navigation purposes. It is concluded that the proposed approach can uncover implicit entities and contribute to extract required information from the existing datasets.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_645998152-beopen1273-2209-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://europepmc.org/articles/PMC5712863 http://europepmc.org/articles/PMC5712863] under the license https://creativecommons.org/licenses/by

* [https://dx.doi.org/10.3390/s17112498 https://dx.doi.org/10.3390/s17112498]

* [https://www.mdpi.com/1424-8220/17/11/2498/pdf https://www.mdpi.com/1424-8220/17/11/2498/pdf]

* [http://www.mdpi.com/1424-8220/17/11/2498/pdf http://www.mdpi.com/1424-8220/17/11/2498/pdf],
: [http://dx.doi.org/10.3390/s17112498 http://dx.doi.org/10.3390/s17112498] under the license cc-by

* [https://dblp.uni-trier.de/db/journals/sensors/sensors17.html#Mobasheri17 https://dblp.uni-trier.de/db/journals/sensors/sensors17.html#Mobasheri17],
: [https://core.ac.uk/display/120133194 https://core.ac.uk/display/120133194],
: [https://doi.org/10.3390/s17112498 https://doi.org/10.3390/s17112498],
: [https://academic.microsoft.com/#/detail/2765193906 https://academic.microsoft.com/#/detail/2765193906] under the license https://creativecommons.org/licenses/by/4.0/

* [https://www.mdpi.com/1424-8220/17/11/2498 https://www.mdpi.com/1424-8220/17/11/2498],
: [https://doaj.org/toc/1424-8220 https://doaj.org/toc/1424-8220]

* [ ]

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Mobasheri 2017a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 645998152 to Mobasheri 2017a

Scipediacontent: Created page with " == Abstract == Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available within the emerging “Big Data”..."