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

Semantic Modelling

Literally, semantics is the study of the meaning. It extracts meanings from phrases, words, sentences, symbols and other modes of information and communication methods through the underlying relationships with the components within. 

The evolution of the Semantic Web technology has re-introduced semantics to Information technology. Semantics now has become important component in managing huge and diverse datasets. The logical expression of meaning brings in machines to assist humans in Information management. The abstraction of the real world can be defined through such logical expressions expressed in a model. Such semantic models are foundations to the Semantic Web applications.

The semantic model defines knowledge behind it. Knowledge has traditionally been used in achieving higher degree of data interoperability. Besides data interoperability, other potential we at i3Mainz see is its underlying capabilities to infer knowledge to discover new knowledge. We have successfully implemented semantic technology in our research activities. 

 

Contact Person

Prof. Dr.-Ing. Frank Boochs

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

Projects

Das Projekt Digitale Edition der Keilschrifttexte aus Haft Tappeh widmet sich der Transliteration und digitalen Bereitstellung von mehr als 600 Keilschrifttexten aus Haft Tappeh (I...
Ziel des Projektes ist es, eine Linked Data Infrastruktur am Bundesamt für Kartographie und Geodäsie anhand von einigen ausgewählten Datenbeständen aufzusetzen und zu integrieren....

Publications

i3mainz - Jahresbericht 2018

2019

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Jahrebericht 2018

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


Evaluating linked data location based services using the example of Stolpersteine

2019

RTF

15th International Conference on Location Based Services (LBS 2019) 11–13 November 2019, Vienna, Austria G. Gartner and H. Huang

In this publication we introduce a linked data powered application which assists users to find so-called Stolpersteine, stones commemorating Jewish victims of the second world war. We show the feasibility of a dedicated location based service as an app using linked data resources and evaluate this approach against local data sources gathered by communities to find out if the current linked data environment can equally and/or sufficiently support an application in this knowledge domain.


Connected Semantic Concepts as a Base for Optimal Recording and Computer-Based Modelling of Cultural Heritage Objects

2019

RTF

Structural Analysis of Historical Constructions

3D and spectral digital recording of cultural heritage monuments is a common activity for their documentation, preservation, conservation management, and reconstruction. Recent developments in 3D and spectral technologies have provided enough flexibility in selecting one technology over another, depending on the data content and quality demands of the data application. Each technology has its own pros/cons, suited perfectly to some situations and not to others. They are mostly unknown to humanities experts, besides having a limited understanding of the data requirements demanded by the research question. These are often left to technical experts who again have a limited understanding of cultural heritage requirements. A common point of view has to be achieved through interdisciplinary discussions. Such agreements need to be documented for their future references and re-uses. We present a method based on semantic concepts that not only documents the semantic essence of such discussions, but also uses it to infer a guidance mechanism that recommends technologies/technical process to generate the required data based on individual needs. Experts' knowledge is represented explicitly through a knowledge representation that allows machines to manage and infer recommendations. First, descriptive semantics guide end users to select the optimal technology/technologies for recording data. Second, structured knowledge controls the processing chain extracting and classifying objects contained in the acquired data. Circumstantial situations during object recording and the behaviour of the technologies in that situation are taken into account. We will explain the approach as such and give results from tests at a CH object.


Identification and classification of objects in 3D point clouds based on a semantic concept

2019

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Modélisation sémantique et logique pour une simulation multi-agent dans le contexte de gestion de catastrophe

2019

RTF

Spatial Analysis and Geomatics (SAGEO) 2019

Disaster management requires both individual and collaborative preparedness among the various stakeholders.
Collaborative exercises aim to train stakeholders to apply the plans prepared and to identify potential problems and areas for improvement. As these exercises are costly, computer simulation is an interesting tool to evaluate preparation through a wider variety of contexts.
However, research on simulation and disaster management focuses on a particular problem rather than on the overall assessment of the plans prepared. This limitation is explained by the challenge of creating a simulation model that can represent and adapt to a wide variety of plans from various disciplines.
The work presented in this paper addresses this challenge by adapting the simulation model based on disaster management information and plans integrated into a knowledge base. The simulation model created is then automatically programmed to perform simulation experiments to improve action plans.
The results of the experiments are analyzed in order to generate new knowledge and know-how to enrich disaster management plans in a virtuous cycle.
This paper presents a proof of concept on the French national Novi plan, for which simulation experiments have made it possible to know the impact of the distribution of doctors on the application of the plan as well as to identify their distribution.


Semantische Geoinformationssysteme: Integration heterogener Geodaten am Beispiel XErleben

2018

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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

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Automatic Integration of Spatial Data into the Semantic Web

2017

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.