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

The so-called African Red Slip Ware (ARS) is a central archaeological object type for the understanding of late antique worlds of ideas and their change, as well as for the economi...
Die sogenannte African Red Slip Ware (ARS) ist eine zentrale archäologische Objektgattung für das Verständnis spätantiker Vorstellungswelten und ihres Wandels, wie auch für die Wir...

Publications

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

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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

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

2017

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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

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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

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How to optimally record cultural heritage objects? Decision support through connected knowledge.

2017

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EVA Berlin 2017. Elektronische Medien & Kunst, Kultur und Historie 24. Berliner Veranstaltung der internationalen EVA-Serie Electronic Media and Visual Arts, 2017

Optical recording of material cultural heritage (CH) is a multidisciplinary activity where the understanding of cross-disciplinary semantics is vital for a successful completion. In many cases, a lack of understanding of transdisciplinary semantics slows this process down. The end users who are mostly humanities experts lack the technical knowledge of spatial and spectral recording and could therefore demand more than what is actually required or sufficient for the intended CH application. The negotiations between technical experts and the end users are a tedious process. We present a semantic-based decision support system, COSCHKR, that employs reasoning and recommends optimal recording technology(ies) according to the application requirements of the recorded and processed data. COSCHKR is an ontology-based knowledge model that implies the development of semantic technologies within the Semantic Web framework. It represents formalized knowledge of the disciplines involved in the process of optical recording of material CH. The paper describes the applicability of the model in spatial, spectral, and visualization applications and summarises current possibilities and challenges.