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    <title language="eng">Identifying enabler and relational ontology networks in design for digital fabrication</title>
    <abstract language="eng">As use of digital fabrication increases in architecture, engineering and construction, the industry seeks appropriate management and processes to enable the adoption during the design/planning phase. Many enablers have been identified across various studies; however, a comprehensive synthesis defining the enablers of design for digital fabrication does not yet exist. This work conducts a systematic literature review of 59 journal articles published in the past decade and identifies 140 enablers under eight categories: actors, resources, conditions, attributes, processes, artefacts, values and risks. The enablers’ frequency network is illustrated using an adjacency matrix. Through the lens of actor-network theory, the work creates a relational ontology to demonstrate the linkages between different enablers. Three examples are presented using onion diagrams: circular construction focus, business model focus and digital twin in industrialisation focus. Finally, this work discusses the intersection of relational ontology with process modelling to design future digital fabrication work routines.</abstract>
    <parentTitle language="eng">Automation in construction</parentTitle>
    <identifier type="doi">10.1016/j.autcon.2022.104592</identifier>
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    <author>Ming Shan Ng</author>
    <author>Daniel Hall</author>
    <author>Marc Schmailzl</author>
    <author>Thomas Linner</author>
    <author>Thomas Bock</author>
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      <language>eng</language>
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      <value>digital fabrication</value>
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  <doc>
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    <title language="eng">Identifying enablers and relational ontology networks in design for digital fabrication</title>
    <abstract language="eng">As use of digital fabrication increases in architecture, engineering and construction, the industry seeks appropriate management and processes to enable the adoption during the design/planning phase. Many enablers have been identified across various studies; however, a comprehensive synthesis defining the enablers of design for digital fabrication does not yet exist. This work conducts a systematic literature review of 59 journal articles published in the past decade and identifies 140 enablers under eight categories: actors, resources, conditions, attributes, processes, artefacts, values and risks. The enablers' frequency network is illustrated using an adjacency matrix. Through the lens of actor-network theory, the work creates a relational ontology to demonstrate the linkages between different enablers. Three examples are presented using onion diagrams: circular construction focus, business model focus and digital twin in industrialisation focus. Finally, this work discusses the intersection of relational ontology with process modelling to design future digital fabrication work routines.</abstract>
    <parentTitle language="eng">Automation in Construction</parentTitle>
    <identifier type="doi">10.1016/j.autcon.2022.104592</identifier>
    <identifier type="issn">0926-5805</identifier>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Ming Shan Ng</author>
    <author>Daniel Hall</author>
    <author>Marc Schmailzl</author>
    <author>Thomas Linner</author>
    <author>Thomas Bock</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Digital fabrication</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Enablers</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Relational ontology network</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Actor-Network Theory (ANT)</value>
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    <subject>
      <language>eng</language>
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      <value>Process modelling</value>
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  <doc>
    <id>3605</id>
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    <publishedYear>2020</publishedYear>
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    <publisherName>The International Association for Automation and Robotics in Construction (I.A.A.R.C.)</publisherName>
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    <title language="eng">Exploring Gerontechnology for Aging-Related Diseases in Design Education: An Interdisciplinary Perspective</title>
    <abstract language="eng">Aging society is not only a crisis in the developed world but also a severe challenge in some emerging economies. However, the awareness of population aging and gerontechnology is far from sufficiently addressed in the architectural design education in universities. Therefore, an interdisciplinary approach in design education is urgently needed to raise the awareness of the aging crisis among the future architects, interior designers, and beyond. This article introduces a novel model of a design seminar offered by a German University, addressing population aging issues in the architecture department. The syllabus, formality, and the expected results of the seminar are revealed in detail. The participants are encouraged to apply interdisciplinary knowledge such as barrier-free architecture, mechanical engineering, electrical engineering, robotics, medicine, psychology, and business to achieve the goals of the seminar. Based on the originality and degree of completion, several students' works are selected and reported, targeting a variety of diseases or syndromes related to aging, such as dementia, immobility, and tremors. Overall, participants of this seminar are motivated and have positive feedback on this seminar, oftentimes claiming that they have seldom studied similar topics in previous architecture education. This enables students from architecture as well as other fields to be better prepared to tackle the upcoming challenges such as labor shortages and infectious diseases in a rapidly aging world. Furthermore, the seminar creates novel concepts that serve as a win-win "honeypot" for both students and their instructors, potentially sparking research topics and start-ups with concepts fostered in this seminar.</abstract>
    <parentTitle language="eng">Proceedings of the 37th International Symposium on Automation and Robotics in Construction (ISARC 2020): From Demonstration to Practical Use, To New Stage of Construction Robot, October 27-28, 2020, Kitakyushu, Japan</parentTitle>
    <identifier type="isbn">978-952-94-3634-7</identifier>
    <identifier type="doi">10.22260/ISARC2020/0102</identifier>
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    <author>Rongbo Hu</author>
    <author>Thomas Linner</author>
    <author>Marc Schmailzl</author>
    <author>Jörg Güttler</author>
    <author>Yuan Lu</author>
    <author>Thomas Bock</author>
    <subject>
      <language>eng</language>
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      <value>aging-related diseases</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Bauhaus 2.0</value>
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      <language>eng</language>
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      <language>eng</language>
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      <value>Dementia</value>
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    <subject>
      <language>eng</language>
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      <value>Design education</value>
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    <subject>
      <language>eng</language>
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      <value>Gerontechnology</value>
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    <subject>
      <language>eng</language>
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      <value>Interdisciplinary</value>
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  <doc>
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    <language>eng</language>
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    <title language="eng">Towards interfacing human centered design processes with the AEC industry by leveraging BIM-based planning methodologies</title>
    <abstract language="eng">Digital workflows in the Architecture, Engineering and Construction (AEC) industry have been working with a wide range of software solutions trying to enable a Design-to-Production (DtP) end-to-end data flow. Thereby, state-of-the-art software solutions attempt to streamline the design and production processes accordingly.&#13;
&#13;
However, most digital workflows lack in terms of adequate sequential data preparation, agglomeration, and interfacing capabilities for consecutive design phases. These issues result in long, tedious correction loops, a wide range of software solutions and extensions to mitigate the issues. In addition, many digital workflows do not consider or integrate construction, production and machine relevant data holistically (respectively geometry and semantics). In this context, the production relevant data in from of human-centered work process data referring to digital human models (DHM), derived human abilities, safety and ergonomic criteria are often neglected. However, this is essential to interface the construction, human and machine relevant data in a holistic manner.&#13;
&#13;
This paper therefore proposes a DtP-workflow which is intended to solve some of the issues by interfacing relevant software solutions incorporating construction, production (including DHM and more) and machine relevant data in a holistic manner using a Building Information Modeling (BIM)-approach (based on the IFC schema). In this regard, the DtP-workflow aims to reverse common top-down digital workflows by considering and integrating the relevant data for consecutive design phases from the beginning. Subsequently, the DtP-workflow should achieve a reduction in planning effort.</abstract>
    <parentTitle language="eng">40th International Symposium on Automation and Robotics in Construction (ISARC 2023): Chennai, India, July 3–9, 2023</parentTitle>
    <identifier type="doi">10.22260/ISARC2023/0045</identifier>
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    <author>Marc Schmailzl</author>
    <author>M. Spitzhirn</author>
    <author>Friedrich Eder</author>
    <author>Georg Krüll</author>
    <author>Mathias Obergrießer</author>
    <author>Thomas Linner</author>
    <author>Wassim Albalkhy</author>
    <author>Zoubeir Lafhaj</author>
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      <language>eng</language>
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      <value>Architecture Engineering and Construction (AEC) industry</value>
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    <subject>
      <language>eng</language>
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      <value>Building Information Modeling (BIM)</value>
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      <language>eng</language>
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      <value>Interoperability</value>
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      <language>eng</language>
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      <value>Digital Human model (DHM)</value>
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    <publisherName>Springer Nature</publisherName>
    <publisherPlace>Cham</publisherPlace>
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    <title language="eng">Exploring the Potential of BIM Models for Deriving Synthetic Training Data for Machine Learning Applications, Montreal</title>
    <abstract language="eng">To increase the efficiency and quality of design and construction tasks, the use of Artificial Intelligence (AI) and Machine Learning (ML) offers a way to automate both repetitive and complex tasks. Many of these ML models rely heavily on large amounts of suitable, machine-readable, and labeled training data. Therefore, a variety of conceivable use cases for ML in the Architecture, Engineering and Construction (AEC) industry are difficult to implement due to a lack of freely and directly usable training data. The process of manually structuring and labeling existing data is time-consuming and needs in some cases skilled personnel to ensure the quality of the labeled data. Due to these factors, approaches for utilizing artificially generated data, referred to as synthetic data, are becoming more prevalent. Since Building Information Models contain a large amount of information, deriving training data from these models presents an obvious route for generation of this data. There are many ML applications whose implementation is inhibited due to a lack of training data, for which model-based synthetic data offer a possible solution approach. The Industry Foundation Classes (IFC) standard provides a powerful exchange format for models independently of their authoring software. Parametric and generative approaches to model creation enable the generation of numerous different building models within a short period of time and with low effort. This paper presents a workflow for automated derivation of synthetic training data from rule-based or parametrically generated models combined with existing IFC datasets as a multimodal data repository. The method is validated by testing automated synthetically labeled image data for a plan detection task, which is carried out with the Object Detection Framework YOLOv8. The suggested workflow has the potential to enhance data accessibility, thereby contributing to the implementation of ML applications in the AEC industry.</abstract>
    <parentTitle language="eng">Advances in Information Technology in Civil and Building Engineering, Proceedings of ICCCBE 2024, Volume 2, Simulation and Automation</parentTitle>
    <identifier type="isbn">9783031873638</identifier>
    <identifier type="issn">2366-2557</identifier>
    <identifier type="doi">10.1007/978-3-031-87364-5_5</identifier>
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    <author>Simon Konrad Hoeng</author>
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    <author>Mathias Obergrießer</author>
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      <language>eng</language>
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      <value>KI</value>
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      <language>eng</language>
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    <subject>
      <language>eng</language>
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    <title language="eng">Towards improving data interoperability for the reconstruction of existing buildings</title>
    <abstract language="eng">Digital representations of buildings are the supporting structures of various use-cases in the emerging field of data-driven decision making. From large scale applications in the context of city planning to the detailed evaluation of critical infrastructure they enable specialists to observe problems, interpret relationships, test solutions virtually and apply them in the real world. This is only feasible if the individual underlying digital model meets the requirements imposed by the analysis at hand.&#13;
In practice, especially models of existing buildings are not easy to come by as the information describing the existing structure is often scattered across multiple different data sources in various formats. Previous research efforts have outlined methodologies which leverage machine learning, computer vision and subsequent semantic enrichment in order to achieve the (re)construction of such building models. However, these methods are generally not integrated with each other, nor do they consider being able to interface with a shared repository of building related data.&#13;
In this paper we present a methodology which focuses on establishing a common context for all building related data by utilizing the Industry Foundation Classes (IFC) schema. In particular we focus on utilizing readily available geometric and semantic data originating from geographic information systems as a basis, subsequently referencing additional data sources in their corresponding context and finally outlining interfaces with downstream enrichment processes in both directions. Through incorporating contextualized (IFC) data into the early stages of the remodeling workflow, we outline an end-to-end process from the initial component-based data-acquisition to the as-built building information model. In establishing a standardized foundation for data exchange and collaboration it enables all stakeholders to work more seamlessly across different stages of the remodeling project.</abstract>
    <parentTitle language="eng">The 20th conference of the International Society for Computing in Civil and Building Engineering (ICCCBE 2024), August 25 to 28, 2024, Montreal</parentTitle>
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    <author>Friedrich Eder</author>
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    <author>Mathias Obergrießer</author>
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