Keywords: Building Information Modelling (BIM), Data Drops, digital transformation, Economic and legal issues, Employer's Information Requirement, General
Astract: In the Architecture, Engineering and Construction (AEC) industry, as well as in the tunnelling domain, inter-company processes between partners in different roles in large-scale construction projects still exhibit great potential towards digitalisation. Thereby, information should be seamlessly shared between partners according to the Building Information Modelling (BIM) paradigm. Today, different types of artefacts (e.g., models, plans, documents, etc.) are shared at different points in time, which differ in terms of requirements, information content, as well as data formats. In this article, we extend and prototypically implement the concept of Data Drops to provide those artefacts in a digitalised form via a shared Data Drop management platform. For this purpose, we have developed a formal, well-defined indexed data structure on a metadata level. This not only facilitates traceability, but also enables searching for specific meta-information and provides a common view on Data Drops. In addition, a networked view between different drops can be provided. The approach is being evaluated on the use case of a real tunnel construction project.

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Keywords: Construction works, Conventional tunneling, digital transformation, documentation process, General, New Austrian Tunneling Method (NATM), software tool, tunnel process management
Astract: The documentation of the tunneling process is a crucial task of every tunnel construction project. It provides evidence of the work performed and thus, serves as a basis for invoicing and for several further analyses. Therefore, continuous digitalisation of this documentation is essential. For this purpose, we provide a digital Tunneling Information Management System (TIMS), which is a prototypically implemented software tool for replacing the still common paper-based documentation process of tunneling projects using the New Austrian Tunneling Method (NATM). The data model presented here defines the data structures managed by this tool. Based on this, the software architecture and the implementation of TIMS is shown.

Keywords: Internet of Production, Industry 4.0, Digital Shadow, Digital Twin, Smart Production

Keywords: conceptual modeling, model-driven engineering, model transformation, graph-based analysis, knowledge graphs
Astract: Core assets of enterprise architecture (EA) are its models. They encapsulate enterprise structure and IT knowledge by providing a holistic view of an organization that can drive decision-making. For making good decisions, it is necessary to have an excellent overview and to know how to analyze the model to gain information that different business stakeholders need. From the perspective of history, EA has evolved a lot, and the models have become larger and more complex. Models’ change in size and complexity requires other techniques to analyze the model since the analysis of models in their raw form can exceed human capabilities by far. Therefore current approaches focus on studying partial views over the model, thus providing a partial valuation. This thesis proposes a slightly different approach to cope with EA analysis. The method is based on transforming conceptual models into graphs and analyzing the model in a graph-based manner by using knowledge and possibilities from graph theory. To put this into the real world, we have developed a generic framework and implemented it in the prototype platform, which we call CM2KG. The platform allows analysts to upload different models created in industry-standard tools and transform them into a standardized graph format. From there on, it becomes possible for them to visualize and interact with the model using multiple techniques, query the whole model, and define custom functions that will provide valuable information. We discuss some basic examples for each part to scratch the surface of what is possible. We also put one existing application of EA analysis into the perspective of this approach by implementing queries that are used to identify smells in EA models.

Keywords: Conceptual Modeling, Semantic Web, Ontology, Systematic Mapping Study, Web Knowledge Base, Knowledge Graphs, Linked Data
Astract: Conceptual models aim to represent real systems at a higher abstraction level. The Semantic Web intends to add meaning to any kind of data formats to arrive at linked data. Taken together, both of them help facilitate data processing and integration for humans as well as for machines. This thesis analyzes the publication landscape at the intersection of conceptual modeling and Semantic Web in the form of a systematic mapping study (SMS). In line with the SMS, the research scope is defined, the search queries are executed, and the publications are screened from an initial number of 5107 to finally 484 papers. Then publications are extracted and mapped according to a series of previously developed taxonomies. The extracted and refined data is analyzed in several analysis steps comprising bibliographical, content, combined taxonomy as well as research community analyses. Threats to validity, and implications for future research from this first SMS regarding the intersection of conceptual modeling and Semantic Web are additionally considered.

Keywords: Augmented Reality, Tunneling
Astract: Tunnel construction is one of the remaining fields that still rely heavily on paper-based processes. Creating paper-based documentation is time-consuming and error-prone. Digitalization can considerably improve these processes. Augmented reality (AR) is one technology that could contribute to this endeavour.AR can deliver information for specific positions in a tunnel through localization automatically. Another benefit of AR is locating virtual information in a real tunnel environment. Due to the large extent of tunnel structures, other technologies for position determination are often inefficient. Despite the enormous benefits of AR, there is little research on this technology in tunnel construction. Therefore, it is unclear whether AR solutions apply to such processes and how to implement them. In this thesis, a focus group interview provided findings on problems in tunnel construction that are improvable with AR. Based on the focus group interview, we selected two problems to improve through AR. We developed two high-fidelity prototypes for the HoloLens 2 to solve these problems: acceptance inspection and tunnel face mapping. Additionally, we developed a solution for localization in the tunnel, which both prototypes utilize. Usability tests give qualitative answers about the usability of the developed prototypes. The tests revealed that usable AR solutions are implementable with current hardware. However, some geometry and user input detection issues by the HoloLens still exist that make it not yet practical enough in real work environments. Furthermore, localization in tunnels with the HoloLens is possible. Regardless, more extensive tests are required to confirm the results for real tunnel construction projects. This thesis serves as a starting point for future research on AR in tunnel construction by providing insights into usability and guidelines for implementing such solutions.

Keywords: data integration, information exchange, semantics
Astract: Data models are the backbone of digital information exchange, since they contain the structure of data to be exchanged. Just as information requirements vary, so do data models - in level of detail, level of abstraction, and domain coverage. Due to these differences, communication between some data models is easy and between others is difficult. Regarding the Building Information Model (BIM) initiative, the IFC standard data model varies in detail, abstraction level, and large domain coverage. In contrast, the Austrian ÖGG-guideline has a consistent detail and abstraction level focusing on a single domain, subsurface engineering. In order to participate in a loss- and distortion-free information exchange, a reliable translation via a multitude of data models is a must-have. In this paper, we present formal criteria for distinguishing between semantics-carrying data models, such as IFC and ÖGG, and translating data models that provide reliable communication bridges between them, such as CAEX and SIMULTAN. We will show that translating data models are an indispensable part of the data model infrastructure even within a single domain. For evaluation purpose, we demonstrate our approach on a subsurface engineering use case.

Keywords: DEMO, Enterprise ontology, Low code, MBE, Mendix
Astract: Due to factors such as hyper-competition, increasing expectations from customers, regulatory changes, and technological advancements, the conditions in which enterprises need to thrive become increasingly turbulent. As a result, enterprise agility, or flexibility, becomes an increasingly important determinant for enterprise success. Since Information System (IS) development often is a limiting factor in achieving enterprise flexibility, enterprise flexibility and (automated) IS flexibility cannot be viewed separately and choices that regard flexibility should not be left to developers. By taking a Model-based Engineering (MBE) approach, starting from ontological models of the enterprise and explicit organization design decisions, we bridge the gap from organizational flexibility to (automated) IS flexibility, in such a way that IT is no longer the limiting factor for enterprise flexibility. Low-code technology is a growing market trend that builds on MBE concepts. In this paper, we report on an mapping for (the automation of) the creation of a Mendix low-code application from the ontological model of an enterprise, while also accommodating the required organizational implementation flexibility. Even though the algorithm has been tested successfully on multiple cases, supporting all possible organizational flexibility seems to be an NP -hard problem, and more research is required to check the feasibility and usability of this approach.

Keywords: Acceptance tests, Distributed systems, Selenium, Software testing, Web testing
Astract: Acceptance tests are used to ensure that a software system delivers its required functionality. They are performed on a system prior to its delivery to a live environment. Acceptance testing becomes a complex task when the system under test (SUT) is distributed, i.e. it consists of multiple applications interacting with each other. The main challenge lies in the synchronization and administration of the test process. Automating acceptance tests of such systems can result in high effort when not performed in a structured way. Control center solutions for handling and managing emergency calls are highly distributed and complex systems. They are usually embedded into an existing infrastructure of services (like telephony call lines, radio communication systems and 3rd party clients). Hence, automating acceptance tests for control center solutions requires simulation on multiple interfaces. As no suitable tool is available for testing control center solutions, Frequentis developed an acceptance test automation framework. With this framework, it is possible to control all necessary communications with the SUT in a uniform and simple way. However, it is only capable of addressing Java Swing based front-ends. As more and more applications become accessible via web interfaces, Frequentis’ control center solutions also offer web based clients to enable emergency call handling via a browser. Therefore the existing test automation framework is required to also address web front-ends. In this master thesis, we extended this framework so that web front-ends participating in a distributed system can be addressed and tested. We collected the necessary requirements, designed and implemented a solution which integrates into the existing framework. This framework extension offers an API to encourage test developers to apply the page object pattern in order to create maintainable tests. Our extension is based on the browser automation tool Selenium. We used requirements engineering to determine the necessary capabilities of the extension. Furthermore, we performed evolutionary prototyping to develop and integrate the extension into the existing framework. Eventually, we performed a case study to evaluate whether the extended test automation framework fits its intended purpose. Our study shows that the extension is used in numerous projects within Frequentis and that there is a high adoption rate of the offered API.