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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLII-4-W18-721-2019</article-id>
<title-group>
<article-title>INTEGRATION OF MOBILE GIS AND LINKED DATA TECHNOLOGY FOR SPATIO-TEMPORAL TRANSPORT DATA MODEL</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Margan</surname>
<given-names>B.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hakimpour</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran</addr-line>
</aff>
<pub-date pub-type="epub">
<day>18</day>
<month>10</month>
<year>2019</year>
</pub-date>
<volume>XLII-4/W18</volume>
<fpage>721</fpage>
<lpage>724</lpage>
<permissions>
<copyright-statement>Copyright: © 2019 B. Margan</copyright-statement>
<copyright-year>2019</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W18-721-2019.html">This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W18-721-2019.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W18-721-2019.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-4-W18-721-2019.pdf</self-uri>
<abstract>
<p>Linked Data is available data on the web in a standard format that is useful for content inspection and insights deriving from data through semantic queries. Querying and Exploring spatial and temporal features of various data sources will be facilitated by using Linked Data. In this paper, an application is presented for linking transport data on the web. Data from Google Maps API and OpenStreetMap linked and published on the web. Spatio-Temporal queries were executed over linked transport data and resulted in network and traffic information in accordance with the user’s position. The client-side of this application contains a web and a mobile application which presents a user interface to access network and traffic information according to the user’s position. The results of the experiment show that by using the intrinsic potential of Linked Data we have tackled the challenges of using heterogeneous data sources and have provided desirable information that could be used for discovering new patterns. The mobile GIS application enables assessing the profits of mentioned technologies through an easy and user-friendly way.</p>
</abstract>
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