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

Semantische Modellierung

Semantik wird auch als Bedeutungslehre bezeichnet. Es extrahiert Bedeutungen von Wörtern, Sätzen, Phrasen, Symbolen und andere Formen der Information durch die zugrunde liegenden Beziehungen der Komponenten zueinander.

Die Entwicklung des Semantischen Webs hat die semantischen Modellierung in der Informationstechnologie revolutioniert. Semantische Modellierung als wichtige Komponente bei der Verwaltung großer und vielfältiger Datenmengen gewinnt zunehmend an Bedeutung. Logische Ausdrücke bringen Maschinen dazu den Menschen in der Informationsverarbeitung zu unterstützen. Die Abstraktion der realen Welt kann durch Modelle ausgedrückt definiert werden. Solche semantischen Modelle sind Grundlagen von Semantic Web Anwendungen die unser Institut erarbeitet.

Das semantische Modell definiert Wissen im Hintergrund und schafft somit einen höheren Grad an Interoperabilität von Daten. Neben der Interoperabilität von Inforamtionen erforscht das i3mainz weitere Potentiale um mit Hilfe der Sematik Wissen abzuleiten und dabei neues Wissen zu entdecken. Erfolgreich werden semantische Technologien in verschiedenen Forschungsprojekten umgesetzt.

Ansprechpartner

Prof. Dr.-Ing. Frank Boochs

Tel.: +49 6131-628-1432
Fax.: +49 6131-628-91432

Projekte

The aim of the project is the documentation of the physical cultural heritage within Kathmandu Valley, espacially the monastic courtyards and the arcaded rest houses. Funded by Arc…
Die sogenannte African Red Slip Ware (ARS) ist eine für das Verständnis spätantiker Vorstellungswelten und ihres Wandels, wie auch für die Wirtschaftsgeschichte zentrale archäologi…

Publikationen

i3mainz - Jahresbericht 2018

2019

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Jahrebericht 2018

Im Jahresbericht werden die Projekte und Aktivitäten des i3mainz in komprimierter Form vorgestellt.


Semantische Geoinformationssysteme: Integration heterogener Geodaten am Beispiel XErleben

2018

T. Homburg; C. Prudhomme; F. BOOCHS

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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.


Semantische Geoinformationssysteme: Integration und Management von heterogener Geodaten

2018

T. Homburg; C. Prudhomme; F. BOOCHS

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Automatic Integration of Spatial Data into the Semantic Web

2017

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

RTF

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.


Katastrophenmanagement: Die geflutete Stadt

2017

C. Prudhomme

RTF

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Towards the design of respond action in disaster management using knowledge modeling

2017

C. Prudhomme; A. Roxin; C. Cruz; F. Boochs

RTF

The Fourth International Conference on Information Systems for Crisis Response and Management in Mediterranean Countries (ISCRAM-med 2017)

This position paper highlights current problems linked to the aspects of the multi-agency collaboration during disaster response. The coordination and cooperation depend on the information sharing and use which must face up to interoperability, access rights, and quality problems. The research project aims at providing an assessment of information impact on the disaster response in order to support the decisionmaking about what information shared or what quality of data used to improve the response efficiency. Our research approach propose to combine an information system able to integrate heterogeneous data and a simulation system to assess different strategies of information sharing, dissemination and use. A knowledge base is used as a bridge between information system and simulation system. This knowledge base allows for designing dynamically a simulation according to open data and for managing the own knowledge and information known by each agent.


Ontology-based Knowledge Representation for Recommendation of Optimal Recording Strategies - Photogrammetry and Laser Scanning as Examples.

2017

S. Wefers

RTF

gis.Science

Experts’ knowledge about optical technologies for spatial and spectral recording is logically structured and stored in an ontology-based knowledge representation with the aim to provide objective recommendations for recording strategies. Besides operational functionalities and technical parameters such as measurement principles, instruments, and setups further factors such as the targeted application, data, physical characteristics of the object, and external influences are considered creating a holistic view on spectral and spatial recording strategies. Through this approach impacting factors on the technologies and generated data are identified. Semantic technologies allow to flexibly store this knowledge in a hierarchical class structure with dependencies, interrelations and description logic statements. Through an inference system the knowledge can be retrieved adapted to individual needs.


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

2017

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

RTF

gis.Science