Professor Dr. Kai-Christian Bruhn, Professor am Fachbereich Technik an der Hochschule Mainz, wurde am 5. Dezember 2017 in der Akademie der Wissenschaftenâ€¦
Wie aus der Zeit gefallen ragt das Brandungskliff am Steigerberg aus einer stillgelegten Kiesgrube zwischen den Ortschaften Eckelsheim und Wendelsheim imâ€¦
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.
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.
This paper addresses the factors that conditioned the choices in lithic resource procurement for tool making at the Late Aurignacian site of Stratzing-Galgenberg (Austria), based on the lithic assemblage from the main area of the site. The raw materials used in the analysed assemblage are varied and partly relate to various local and non-local proveniences. The importance of non-local flint in the assemblage contradicts the distance decay model according to which the amount of a given raw material decreases with the increasing distance from its source. Drawing on the approach developed recently by Lucy Wilson, we examine the predictive ability of â€śsource attractivenessâ€ť with respect to terrain difficulty and energy expenditure to understand why some sources were used more than others, using a Geographic Information System (GIS). Our results indicate that terrain difficulty and mobility costs matter and have a better predictive ability than Euclidean distance alone to explain assemblage variability in the Aurignacian of the Middle Danube region.
Expertsâ€™ 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.
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.
Das Vorhaben hatte zum Ziel, ein wirtschaftliches Verfahren zur Erstellung von GebĂ¤udeplĂ¤nen zu untersuchen. So wurde durch die Gruppe eine 3D-Erfassung und Auswertung mittels handgefĂĽhrtem Low-Cost Scannersystem in Form der
Sensorleiste Kinect durchgefĂĽhrt. Die abgeleiteten PlĂ¤ne kĂ¶nnen neben der Indoor-Navigation u.a. auch zu Zwâ€¦
Michael MĂĽller (B. Sc.),
Fabian Schmenger (B. Sc.),
Daniel SchrĂ¶der (B. Sc.),
Kira Zschiesche (B. Eng.)
Im dritten Semester des Masterstudiengangs Geoinformatik und Vermessung ist von den Studierenden ein Projekt als Gruppenarbeit im Rahmen von ca. 540 Arbeitsstunden pro Studierendem durchzufĂĽhren. Es besteht die MĂ¶glichkeit fĂĽr die Studierenden wĂ¤hrend einer solchen Projektphase neuartige und alternative Auswerteverfahren fĂĽr bestehendeâ€¦
Studierende des Masterstudiengangs Geoinformatik und Vermessung
Im Rahmen des Mastermoduls "InterdisziplinĂ¤re Anwendungen raumbezogener Informationstechnik" in den StudiengĂ¤ngen "Geoinformatik und Vermessung" (HS Mainz) und "ArchĂ¤ologie" (JGU Mainz) findet am 4. Dezember 2014 ein Workshop statt. Das mit dem "Open Humanities Award" der EU-Initiative DM2E (Digitised Manuscripts to Europeana) ausgezeiâ€¦