Institut für Raumbezogene Informations- und Messtechnik
Hochschule Mainz - University of Applied Sciences

Suche

Homburg, Timo

Projekte

2015

The SemGIS project aims at interpreting heterogeneous data by creating interoperability via a semantic layer between former unrelated spatial and non-spatial data sets. Applications of this semantic layer are to be found in disaster management,…

Nachrichten

2018

Am Samstag, dem 27. Oktober, startete mit einem großen Kick-Off in Mainz der Kulturhackathon Coding Da Vinci Rhein-Main, unter anderen organisiert von mainze…

2017

Auf dem 16. Mainzer Wissenschaftsmarkt am 9. und 10. September 2017, zu dem die Mainzer Wissenschaftsallianz unter dem Motto Mensc…

Bei der Konferenz WEBIST 2017, der 13th International Conference on Web Information Systems and Technologies, die vom 25.-27. Apri…

Publikationen

2018

Semantische Geoinformationssysteme: Integration heterogener Geodaten am Beispiel XErleben

2018

Timo Homburg, Claire Prudhomme, Frank BOOCHS

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<p>This poster has been presented during the conference Der Fachaustausch Geoinformation (http://www.fachaustausch-geoinformation.de/) organized by GeoNet.MRN to exhibit the semantic geographic information system developed in the context of SemGIS project. The poster shows the approaches used to integrate heterogeneous data sets from different sources. These data sets can then, be enriched through resources from the Semantic Web. An example of such enrichment is presented from an integrated XErleben data. Finally, it illustrates the functionalities of the system to query and visualize data, but also the downlift of selected data according to different standardized formats.</p>

Semantische Geoinformationssysteme: Integration und Management von heterogener Geodaten

2018

Timo Homburg, Claire Prudhomme, Frank BOOCHS

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2017

Automatic Integration of Spatial Data into the Semantic Web

2017

Claire Prudhomme, Timo Homburg, Jean-Jacques Ponciano, F Boochs, Roxin, Ana, Cruz, Christophe

WebIST 2017
<p><span class="foldable-text" data-reactid="122" id="yui_3_14_1_1_1505396336545_1222">For several years, many researchers tried to semantically integrate geospatial datasets into the semantic web. Although, there are many general means of integrating interconnected relational datasets (e.g. R2RML), importing schema-less relational geospatial data remains a major challenge in the semantic web community. In our project SemGIS we face significant importation challenges of schema-less geodatasets, in various data formats without relations to the semantic web. We therefore developed an automatic process of semantification for aforementioned data using among others the geometry of spatial objects. We combine Natural Language processing with geographic and semantic tools in order to extract semantic information of spatial data into a local ontology linked to existing semantic web resources. For our experiments, we used LinkedGeoData and Geonames ontologies to link semantic spatial information and compared links with DBpedia and Wikidata for other types of information. The aim of our experiments presented in this paper, is to examine the feasibility and limits of an automated integration of spatial data into a semantic knowledge base and to assess its correctness according to different open datasets. Other ways to link these open datasets have been applied and we used the different results for evaluating our automatic approach.</span></p>

Integration, quality assurance and usage of geospatial data with semantic tools

2017

Timo Homburg, Claire Prudhomme, F Boochs, Ana Roxin, Christophe Cruz

gis.Science









2016

Interpreting Heterogenous Geospatial Data using Semantic Web Technologies

2016

Timo Homburg, Claire Prudhomme, Falk WĂĽrriehausen, A Karmacharya, F Boochs, Christophe Cruz, Ana-Maria Roxin

Computational Science and Its Applications -- ICCSA 2016
<p>The paper presents work on implementation of semantic technologies within a geospatial environment to provide a common base for further semantic interpretation. The work adds on the current works in similar areas where priorities are more on spatial data integration. We assert that having a common unified semantic view on heterogeneous datasets provides a dimension that allows us to extend beyond conventional concepts of searchability, reusability, composability and interoperability of digital geospatial data. It provides contextual understanding on geodata that will enhance effective interpretations through possible reasoning capabilities. &nbsp;We highlight this through use cases in disaster management and planned land use that are significantly different. This paper illustrates the work that firstly follows existing Semantic Web standards when dealing with vector geodata and secondly extends current standards when dealing with raster geodata and more advanced geospatial operations.</p>

Vorstellung SemGIS Projekt - Einblick und Status

2016

Timo Homburg, Claire Prudhomme

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Interlinking Heterogenous Spatial Data Using an INSPIRE Ontology

2016

Timo Homburg, F. WĂĽrriehausen, H MĂĽller

INSPIRE Conference 2016, Barcelona









Using an INSPIRE Ontology to Support Spatial Data Interoperability

2016

F. WĂĽrriehausen, Timo Homburg, H MĂĽller

INSPIRE Conference 2016, Barcelona