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

Timo Homburg, M. Sc.

Timo Homburg, M. Sc.

Fachbereich Technik –
Geoinformatik & Vermessung
Raum: C1.17
Telefon: +49 6131-628-1467
Fax: +49 6131-628-91467

Funktionen

  • – Wissenschaftlicher Mitarbeiter

Forschung

Anzeigename: 
Timo Homburg, M. Sc.

E-Mail

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Telefon: 
+49 6131-628-1467
Fax: 
+49 6131-628-91467
Raum: 
C1.17
Funktionen: 
Wissenschaftlicher Mitarbeiter

Projekte

The SemGIS project aims at interpreting heterogeneous data by creating interoperability via a semantic layer between former unrelated spatial and non-spatial data sets.…

Publikationen

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

2017

Homburg, T.,
Prudhomme, C.,
Boochs, F.,
Roxin, A.,
Cruz, C.

BibTex

gis.Science

Automatic Integration of Spatial Data into the Semantic Web

2017

Prudhomme, C.,
Homburg, T.,
Ponciano, J.J.,
Boochs, F.,
Roxin, A.,
Cruz, C.

BibTex

WebIST 2017

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.


Using an INSPIRE Ontology to Support Spatial Data Interoperability

2016

Würriehausen, F.,
Homburg, T.,
Müller, H.

BibTex

INSPIRE Conference 2016, Barcelona

Interlinking Heterogenous Spatial Data Using an INSPIRE Ontology

2016

Homburg, T.,
Würriehausen, F.,
Müller, H.

BibTex

INSPIRE Conference 2016, Barcelona

Vorstellung SemGIS Projekt - Einblick und Status

2016

Homburg, T.,
Prudhomme, C.

BibTex

n.A.

Interpreting Heterogenous Geospatial Data using Semantic Web Technologies

2016

Homburg, T.,
Prudhomme, C.,
Würriehausen, F.,
Karmacharya, A.,
Boochs, F.,
Cruz, C.,
Roxin, A.M.

BibTex

Computational Science and Its Applications -- ICCSA 2016

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.  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.