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: Model Driven Engineering, Model Engineering, Pattern Recognition, Machine Learning, Clustering, Dual Deep Instantiation, Sensor Systems, Model Intelligence, Model Generation, Monitoring Systems
Astract: This thesis examines the possibility of model generation from data sets. Automatic model generation from data sets is a subtopic of Model Intelligence. Model Intelligence aims to combine the benefits of Model Driven Engineering (MDE) with the benefits of machinelearning (ML) techniques. During a workshop about Model Intelligence a call for paper,namely "Model inferencers and automatic model generators from datas ets" [ MDE ]. In this work we propose a method to generate models with the help of machine learning from data sets and make a case study on a real-life data set coming from a sensor system of the (Plus-)Plus-Energy building of the Vienna University of Technology. Different definitions of"model" are considered to answer the question whether or not it is possible to generate models automatically from sensor data with the help of machine learning and data mining techniques.A frequent pattern recognition based method is introduced, which aims to generate a frequent pattern based model for sensors. To set boundaries for model generation, we discuss the basic concepts and introduce key techniques of metamodeling. We choose a suitable technique to define our metamodel, which then will serve as the basis of model generation. During defining the model and exploring different modeling techniques we mainly discuss methods and related concepts conforming to the Meta-Object Facility (MOF).After defining the model, we apply segmentation on the sensor-derived data set, and label different segments according to the Symbolic Aggregate approXimation (SAX) We apply frequent pattern mining on the segmented and labeled data sets. Based on the results of the patternmining, we carry out clustering to help us decide, whether the frequent patterns found in the sensor data are suitable to differentiate between different types of sensors, thus can serve as attributes in model definitions for the different types of sensors.Our results show that depending on what definition of "model" is used, it is possible to generate models either on the M1 or the M0 level of the M4 meta-modeling framework. Furthermore, aproposed model with Double Deep Instantiation (DDI) is feasible to model type definitionsfor the sensors. In conclusion, we show that generating type definitions for the sensors based on their frequent patterns is successful in most cases. We have found some instances with interesting caveats that call for further investigation.ix

Keywords: •Building Information Modelling, Blockchain, Smart Contracts, Ethereum, Construction
Astract: There is a big potential for process optimizations, due to the digitalization gap in the construction business. New digital technologies, as the Building Information Modelling (BIM), are increasingly being adapted by the stakeholders in this area. On the other hand, blockchain is a very new and innovative technology domain which has grown immensely in the last several years, and where people are now trying to find the right use-cases. Especially, the even newer field of smart contract development has opened the door for a large amount of possible applications, where it is neither clear if these can actually be implemented as envisioned, nor if there is even a need for a decentralized solution at all. In a construction project, changes on BIM models are only to be approved by the appropriate stakeholder. Therefore, we have combined the BIM models, which are stored using a Git repository, with a release management workflow, which is realised as a smart contract on the Ethereum blockchain.This enables the workflow to be transparent, traceable and its results to be immutable. The goal of this work is to create a prototype and compare it to other (off-chain) solutions and to evaluate if an application of a combination of BIM and blockchain yields an advantage in terms of costs and security.

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Astract: Starting point/Motivation Studies show that there is significant potential for efficiency gain in energy systems encompassing not just a single building but entire building complexes. However, the expectations of building developers, operators and residents regarding performance (incl. energy cost, comfort, etc.) could not be met. The difficulties in the planning and construction process and the unexpected effects on energy supply systems can generally be traced back to the lack of insight and understanding of complex resource and energy efficient systems and to communication problems among the involved stakeholders. Contents and Objectives Currently, there is a shortage of appropriate tools that support planers during the renovation process of existing buildings or the planning of new buildings. Such tools should enable the development of consistent scenarios encompassing both the energy supply system and the typical behaviour of energy end-consumers. Energy suppliers on the other hand need tools that can take technological innovations in the building sector into account to determine a load and supply behaviour consistent with that of the end-consumers. The project aims to provide support for the optimisation of the planning process both of buildings and of energy supply networks within the context of the entire urban system. Methods The method for classification of energy end-consumer behaviour in an urban environment developed in project Simultan determines the spatial distribution of typical behaviours by means of a survey and by subsequently aggregating the findings according to region, residential unit and net living space area. Significant parameters of the various behaviour types were evaluated and compared within their urban context. Subsequently those parameters were analysed and their significance with regard to the "resident-sensitive" modelling of the energy end-consumer in urban areas was determined. This analysis provided the foundation for the definition of multiple development scenarios for the urban energy supply systems considering the potential of building technology. The impact of the various tariff models on the total cost of heat supply for single residential buildings in three categories as well as the resulting designs of new tariff models were tested. The requirement for support of an integral, simultaneous planning process of optimised building complexes resulted in the development of a tool for decision support on the level of a single building as well as on the level of a building complex. The design process was iterative and ran in cooperation with specialist planers in the areas of architecture, building physics and building services. This resulted in the design of data models and algorithms for comparative evaluation and analysis of technical measures for increasing the resiliency and efficiency of buildings while staying within the limits of pre-defined cost parameters. The interactive aspect of the planning process was tested within the context of several scenarios and optimized for efficiency and for compliance with the liability and warranty regulations. One residential and one office building were the main use cases for evaluating the tool in regard to the design of a ventilation system, the display and editing of geometry, the placement of components, the calculation of various system parameters (e.g. U value, pressure loss, shading, thermal loads, etc.), as well as the translation to external data models. Results The main result of project Simultan is the development of a decision support system for simultaneous integrated multi-disciplinary planning of highly energy efficient building complexes, which can be utilised additionally as an analysis and fine-tuning tool for energy supply network planning. The simulations on an urban level generated as part of the project were used as the basis for the design of multiple urban energy supply network development scenarios. These contributed to the improved understanding of the urban energy landscape and, consequently, to the development of new tariff models serving as additional motivation for finding efficient energy solutions in building development. Novel metrics for detecting malware in networks and a list of corresponding countermeasures were devised in the area of cyber security. The resulting complex informational landscape is presented in a web based information visualisation tool that incorporates multiple levels of detail - from a single building to an entire urban district. Furthermore, a tool for interactive integrated planning was implemented. It uses the geometry as one of the main interfaces for information exchange between different components of the data model belonging to the various stakeholders. Neighbourhood relationships, aggregation, limited-by or contained-in relationships are thus automatically translated into data structures. The tool enables the definition of calculations based on component parameters, network topology, zone, building or building complex groups. Those can be based on elementary mathematical functions, graph evaluations within networks, or on complex web based simulations. The tool uses its own data model. It is a linked hierarchical component collection - a component can have parameters, calculations and sub-components and an arbitrary number of other components can reference each component. The tools offers an upgradable translation service that enables the user to define a mapping between (parts of) this internal data model and (parts of) external data models of varying complexity. This facilitates the communication with external specialized tools. An interface to an individually configurable GIT server allows version control and support of project data managed by multiple stakeholders. Prospects / Suggestions for future research The tools developed in the context of project Simultan have a multitude of interfaces. Their number can be further expanded by implementing current and future communication and data exchange standards - e.g. BIM. This should enable loss- and distortion-free information exchange with other tools, developed for various other aspects of the planning and management process. Another open question is the timely detection and informative display of conflicts (e.g. several users working on the same wall) and the support of a real-time expert solution by providing appropriate procedures, visualisation and management methods. It is one of the most significant aspects of an efficient interactive planning tool. There are two follow-up projects based on the knowledge gained in project Simultan - one in cooperation with Flughafen Wien Schwechat and a Smart City FFG project. As part of those the interfaces to external tools and the usability of the Simultan tool are being developed further.

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