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

SemanticGIS

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, emergency management and decentralized green energy.
Motivation und Ziele: 

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, emergency management and decentralized green energy. In the context of the german energy transition project, the part of spatial data should not to be underestimated. Data of different kinds are collected constantly in massive amounts in various data formats. As the process of data format standardization can be at best a long term goal, information management systems need to be enabled to cope with heterogeneous data directly in order to simplify communication between existing standards. Crucial problems and lack of efficiency because of data conversion issues arise in the area of flood management because the compatibility of data sources used by authorities, nongovernmental organizations and companies is often nonexistent. In an emergency case, this leads to restrictions in the operational framework of mitigation and therefore to more risks as well as costs. In the context of energy transition, a common task is to plan and distribute energy according to local demands and because of decentralized energy generation also its provision. To quantify those demands, solutions for exchanging and interpreting information from different authorities and companies are important. The SemGIS project‘s motivation is therefore to simplify data interoperability using semantic technologies in order to surpass the aforementioned obstacles completely or to a certain extent.

SemGIS goals are:

– Creating a semantic model which includes Expert knowledge in flood management and emergency management

– Expert knowledge in extraction and distribution of green energy

– Data structures and patterns familiar to the cooperation partners current working environment

– Data interpretation from heterogeneous semantic data and documents for data integration preparation.

– Development of a mechanism to recognize concepts in heterogeneous data and to annotate its meaning

– Extension of the system using description logic to enrich the predefined semantic and to increase its usefulness

– Reasoning in a geospatial context using already existing semantic technologies

– Application of rule-based analysis to support specialists in decision-making processes

Aktivitäten: 
The activity part is divided into the two contributions by the two Phds in the project:
 
Timo Homburg:
 

From January to March of this year the project focused on the extraction of ontologies that are defined by frequently occuring formats we have to deal with like INSPIRE, XPlanung Data and AAA-Data and its manual interlinkage into the Semantic Web. Those results and experiences thereof manifested in our publication at ICCSA2016 in Beijing China in July 2016. From April to June algorithms to automatically integrate geodata of unknown schemas have been developed, its shortcomings analyzed and tests have been conducted on various concerned datasets. After an evaluation of the different algorithms and a therefore established base interpretation of data, the research focus from August to October shifted towards the integration of provenance and data quality information into the current knowledge base. By integrating provenance and data quality information into the model we can publish this information to the Semantic Web where such information is rare and we can evaluate the accuracy of the results the SemGIS project will produce in the aspects that are important for the end-user. End of September, a poster presentation of the INSPIRE ontology at the annual INSPIRE conference in Barcelona as well as an aural presentation of the matter took place. From October 2016 we began correspondences with two potential new cooperation partners, SteB Köln and the Federal Office for Cartography and Geodesie in Germany. The later of which resulted in a prototype application that highlights quality criteria of OpenStreetMap geometries which are tailormade to the requests of their costumers and their needs (See Figure 2). This prototype will become the basis of one of the PhD thesis being developed in the SemGIS project.

 

Claire Prudhomme:

The activities of the year 2016 can be separated into two main parts. The first part concerns in semantic modelling. In the continuity of the previous year research on existing systems to support the disaster management, we have analyzed the different ontologies used in these systems. This analysis aimed at identifying if we can reuse one or several of these existing ontologies in our project according to their goal and their specificity. We have then, designed a processing to integrate automatically and semantically dataset with unknown schema. The second part concerns in using our semantic geographic system for improving the disaster management. More precisely, we have focused on improving action plans which are prepared for the response to a disaster. These plans are assessed after their application to a disaster or after a training of response actors to a disaster situation. However, some tests of the plans can be inapplicable or have a high cost. That is why, we have decided to combine our semantic geographic information system with a simulation system in order to test the response action plans with a lower cost. In order to realize a such system, we have studied the different existing simulation models in order to determine the most adapted to the requirements of a disaster situation management. The most adapted model is a multi-agent system. That is why, new research has been conducted on multi-agent systems and the different agent modellings. In parallel, a study of different response action plans is realized in order to identify accurately the components of disaster response.

 

Eckdaten

Zeitraum:     01.06.2015 - 31.05.2019
Kooperation:
  • – geomer GmbH
  • – Geocom Informatik GmbH
  • – Universität Koblenz-Landau, WeST
  • – Université Bourgogne Franche-Comté (UBFC), Laboratoire LE2I – UMR CNRS 6306
  • – Bundesministerium für Bildung und Forschung (BMBF)
Förderkennzeichen:      03FH032IX4
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Nachrichten

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

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

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Publikationen

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

n.A.







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.


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







SEMANTIC CATALOGUE TO MANAGE DATA SOURCES IN DISASTER MANAGEMENT SYSTEM

2016

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

RTF

The 15th International Conference on Informatics in Economy 2016

With the climate change, disasters occur more frequently and the need for efficient disaster management systems becomes highly recommended to save lives. This paper deals with a study of existing systems, with the intention of determining the main recent improvement in the domain. The heterogeneous data integration process is a major central point. Thus, a semantic system with three main components is proposed as a new position in the disaster management systems. These three components are a knowledge base, a reasoner and a semantic catalogue. The knowledge base provides a controlled vocabulary and allows storing information retrieval. The semantic catalogue facilitates the access to data sources adapted to user's and agent's needs. The reasoner analyzes the information in the knowledge base thus replying to the user queries. In addition, the reasoner aims at adding automatically new data sources in the semantic catalogue. The fast access to a great number of data sources is of benefit for decision-making systems such as disaster management systems.


Vorstellung SemGIS Projekt - Einblick und Status

2016

T. Homburg,
C. Prudhomme

RTF

n.A.