Johannes Scholz

An Indoor Navigation Ontology for Production Assets in a Production Environment

This article highlights an indoor navigation ontology for an indoor production environment. The ontology focuses on the movement of production assets in an indoor environment, to support autonomous navigation in the indoor space. Due to the fact that production environments have a different layout than ordinary indoor spaces, like buildings for office or residential use, an ontology focusing on indoor navigation looks different than ontologies in recent publications. Hence, rooms, corridors and doors to separate rooms and corridors are hardly present in an indoor production environment. Furthermore, indoor spaces for production purposes are likely to change in terms of physical layout and in terms of equipment location. The indoor navigation ontology highlighted in this paper utilizes an affordance based approach, which can be exploited for navigation purposes. A brief explanation of the routing methodology based on affordances is given in this paper, to justify the need for an indoor navigation ontology.

Spatial Accuracy Evaluation of Population Density Grid Disaggregations with Corine Landcover

The article elaborates on the spatial disaggregation approach of the 1 km population density grid created by the European Forum for Geostatistics in a defined study area where accurate population reference data are available. The chapter presents an approach to disaggregate the population grid to target resolution of 100 and 500 m respectively and describes the evaluation methodology. The resulting population grids are evaluated with respect to the reference population dataset of the Austrian Bureau of Statistics. In addition, the results are evaluated regarding their correlation to the reference or a random population dataset. The results indicate that there is evidence that the disaggregated population grid with 500 m resolution is more accurate than the 100 m population grid. In addition, the 100 m disaggregated population raster shows more correlation with the random population grid. Furthermore, the chapter shows that densely populated zones are estimated with higher accuracy than medium and sparsely populated areas.

Scenario-based Spatial Decision Support for Network Infrastructure Design

This paper describes an extended framework for scenario based spatial decision support for constructing new network infrastructure and its application in the domains of telecommunication, forestry and energy. There is an increasing need to provide new planning paradigms to support very expensive strategic investment decisions in new network infrastructure in these domains. The planning processes are still dominated by an expert approach based on empirical knowledge and manual implementation. With this conventional approach it is impossible to visualize and to consider different planning scenarios within a reasonable cost and time frame. We combined the powerful analytical and visualization capabilities of a Geographic Information System (GIS) with mathematical methods of graph theory and combinatorial optimization. This conceptual approach extends the basic spatial decision support model with a knowledge based module for scenario parameterization and graph generation, a module for geodata integration and processing, an operations research optimization module and a multi-level visualization module supporting the need of different communication channels within the decision making process.

Digital Technologies for Forest Supply Chain Optimization: Existing Solutions and Future Trends

The role of digital technologies for fostering sustainability and efficiency in forest-based supply chains is well acknowledged and motivated several studies in the scope of precision forestry. Sensor technologies can collect relevant data in forest-based supply chains, comprising all activities from within forests and the production of the woody raw material to its transformation into marketable forest-based products. Advanced planning systems can help to support decisions of the various entities in the supply chain, e.g., forest owners, harvest companies, haulage companies, and forest product processing industry. Such tools can help to deal with the complex interdependencies between different entities, often with opposing objectives and actions—which may increase efficiency of forest-based supply chains. This paper analyzes contemporary literature dealing with digital technologies in forest-based supply chains and summarizes the state-of-the-art digital technologies for real-time data collection on forests, product flows, and forest operations, as well as planning systems and other decision support systems in use by supply chain actors. Higher sustainability and efficiency of forest-based supply chains require a seamless information flow to foster integrated planning of the activities over the supply chain—thereby facilitating seamless data exchange between the supply chain entities and foster new forms of collaboration. Therefore, this paper deals with data exchange and multi-entity collaboration aspects in combination with interoperability challenges related with the integration among multiple process data collection tools and advanced planning systems. Finally, this interdisciplinary review leads to the discussion of relevant guidelines that can guide future research and integration projects in this domain.

A Spatio-Temporal Linked Data Representation for Modeling Spatio-Temporal Dialect Data

Collections of linguistic and dialect data often lack a semantic description and the ability to establish relations to external datasets, from e.g. demography, socio-economics, or geography. Based on existing projects—the Database of Bavarian Dialects in Austria and exploreAT!—this paper elaborates on a spatio-temporal Linked Data model for representing linguistic/dialect data. Here we focus on utilizing existing data and publishing them using a virtual RDF graph. Additionally, we exploit external data sources like DBPedia and geonames.org, to specify the meaning of dialect records and make use of stable geographical placenames. In the paper we highlight a spatio-temporal modeling and representation of linguistic records relying on the notion of a discrete lifespan of an object. Based on a real-world example—using the lemma “Karotte” (engl. carrot) we show how the usage of a specific dialect word (“Karottn”) changes from 1916 until 2016—by exploiting the expressive power of GeoSPARQL.

Semantically Annotated Manufacturing Data to support Decision Making in Industry 4.0: A Use-Case Driven Approach

Intelligente Fertigung oder Industrie 4.0 ist ein Schlusselkonzept, um die Produktivitat und Qualitat in industriellen Fertigungsunternehmen durch Automatisierung und datengetriebene Methoden zu erhohen. Intelligente Fertigung nutzt Theorien cyber-physischer Systeme, dem Internet der Dinge sowie des Cloud-Computing. In dieser Abhandlung konzentrieren sich die Autoren auf Ontologie und (raumliche) Semantik, die als Technologie dienen, um semantische Kompatibilitat der Fertigungsdaten sicherzustellen. Zusatzlich empfiehlt die Abhandlung, fertigungsrelevante Daten uber die Einfuhrung von Geografie und Semantik als Sortierformate zu strukturieren. Der in dieser Abhandlung verfolgte Ansatz sichert Fertigungsdaten verschiedener IT-Systeme in einer Graphdatenbank. Wahrend des Datenintegrationsprozesses kommentiert das System systematisch die Daten – basierend auf einer Ontologie, die fur diesen Zweck entwickelt wurde – und hangt raumliche Informationen an. Der in dieser Abhandlung vorgestellte Ansatz nutzt eine Analyse von Fertigungsdaten in Bezug auf Semantik und raumliche Abmessung. Die Methodologie wird auf zwei Anwendungsfalle fur ein Halbleiterfertigungsunternehmen angewendet. Der erste Anwendungsfall behandelt die Datenanalyse zur Ereignisanalyse unter Verwendung von semantischen ˜hnlichkeiten. Der zweite Anwendungsfall unterstutzt die Entscheidungsfindung in der Fertigungsumgebung durch die Identifizierung potentieller Engpasse bei der Halbleiterfertigungslinie.