Proceedings

Permanent URI for this communityhttps://dl.gi.de/handle/20.500.12116/23

In der LNI-Reihe "Proceedings" werden Tagungs- und Workshopbände veröffentlich. Grundsätzlich werden nur Proceedings von solchen Veranstaltungen in den LNI veröffentlicht, an denen eine GI-Gliederung beteiligt ist.

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Authors with most Documents  

Schroeder, Ulrik
79
Lucke, Ulrike
67
Busch, Christoph
59
Thomas, Oliver
58
Theuvsen, Ludwig
57

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Author: search.filters.author.Thomas, Oliver

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1 - 10 of 58
  • Conference Paper
    Designing inclusive learning platforms for ethnic minorities
    (Gesellschaft für Informatik e.V., 2024) Göritz, Lorena; Stattkus, Daniel; Högemann, Malte; Coban, Halilcan; Hauff, Christian; Kolodziej, Katharina; Schmidt, Maike; Thomas, Oliver; Klein, Maike; Krupka, Daniel; Winter, Cornelia; Gergeleit, Martin; Martin, Ludger
    Digital learning platforms are currently being discussed as a means to democratize education, offering less privileged groups the opportunity to advance their careers. Research suggests, however, that some online courses may favor more privileged groups, imposing psychological barriers on minorities. Our study examines these barriers and proposes design principles to promote inclusive digital learning environments for ethnic minorities. By focusing on underrepresented groups, such as ethnic minorities, who have historically faced barriers to the information technology sector due to stereotypes and prejudice, we empower them to engage with digital learning platforms confidently. Developing platforms that reduce stigma is essential to meeting the needs of individuals regardless of ethnicity, religion, or gender. To facilitate the understanding and illustration of the design principles, we implemented them in a software prototype that analyzes learning platforms for inclusivity. Through our findings, we promote equity in learning environments, thereby fostering responsible digital transformation.
  • Conference Paper
    Privacy, Utility, Effort, Transparency and Fairness: Identifying and Swaying Trade-offs in Privacy Preserving Machine Learning through Hybrid Methods
    (Gesellschaft für Informatik e.V., 2024) Eleks, Marian; Ihler Jakob; Rebstadt, Jonas; Kortum-Landwehr, Henrik; Thomas, Oliver; Klein, Maike; Krupka, Daniel; Winter, Cornelia; Gergeleit, Martin; Martin, Ludger
    As Artificial Intelligence (AI) permeates most economic sectors, the discipline Privacy Preserving Machine Learning (PPML) gains increasing importance as a way to ensure appropriate handling of sensitive data in the machine learning process. Although PPML-methods stand to provide privacy protection in AI use cases, each one comes with a trade-off. Practitioners applying PPML-methods increasingly request an overview of the types and impacts of these trade-offs. To aid this gap in knowledge, this article applies design science research to collect trade-off dimensions and method impacts in an extensive literature review. It then evaluates the specific trade-offs with a focus group of experts and finally constructs an overview over PPML-methods and method combinations’ impact. The final trade-off dimensions are privacy, utility, effort, transparency, and fairness. Seven PPML-methods and their combinations are evaluated according to their impact in these dimensions, resulting in a vast collection of design knowledge and identified research gaps.
  • Conference Paper
    Artificial Intelligence-Based Assistance Systems for Environmental Sustainability in Smart Homes: A Systematic Literature Review on Requirements and Future Directions
    (Gesellschaft für Informatik e.V., 2024) Brîncoveanu, Constantin; Carl, K. Valerie; Binz, Simon; Weiher, Moritz-Andre; Thomas, Oliver; Hinz, Oliver; Klein, Maike; Krupka, Daniel; Winter, Cornelia; Gergeleit, Martin; Martin, Ludger
    Artificial Intelligence (AI) is increasingly being utilized to promote sustainable behavior, particularly in the context of smart homes. Such solutions can significantly enhance resource consumption sustainability by leveraging data analysis for ecological benefits. This systematic literature review examines the requirements for data-driven AI applications aimed at improving environmental sustainability in smart homes, based on an analysis of 60 selected papers. Key findings include the importance of predictive analytics, privacy and security, context-aware features, real-time monitoring, interoperability, efficiency strategies, personalized user engagement, user interface design, and behavioral aspects. We highlight technological advancements that facilitate more comprehensive applications and identify the need for integrating diverse features to build consumer trust and acceptance. This review provides an overview of current smart home technologies and suggests future research directions to enhance energy efficiency, user comfort, and environmental sustainability.
  • Conference Paper
    Privacy Aware Processing
    (Gesellschaft für Informatik e.V., 2023) Eleks, Marian; Rebstadt, Jonas; Kortum, Henrik; Thomas, Oliver; Klein, Maike; Krupka, Daniel; Winter, Cornelia; Wohlgemuth, Volker
    In many machine learning (ML) applications, the provision of data and the training as well as the analysis of machine learning systems are performed by distinct actors, a data owner and a data consumer. To protect sensitive information in these ML-scenarios, privacy aware machine learning (PAML) methods are often applied to the data before sharing. Based on the type of PAML methods used, data understanding and preparation as defined in the CRISP-DM model become more difficult if not impossible. To enable these steps, we propose a method to share a variety of uncritical information with the data consumer who is then able to define the necessary processing steps on a meta-level. These are then applied to the data in the data owners local trusted environment before the PAML-methods whereupon the prepared and protected data is shared.
  • Conference Paper
    The Hitchhiker‘s Guide to Urban Spaces
    (Gesellschaft für Informatik e.V., 2023) Heinbach, Christoph; Gösling, Henning; Thomas, Oliver; Klein, Maike; Krupka, Daniel; Winter, Cornelia; Wohlgemuth, Volker
    Urban transportation is increasingly challenged by growing populations and the rapid growth of e-commerce, thus, driving data-driven innovations for sustainable mobility services. Shared mobility consequently emerges as a promising city transport concept, while combined service opportunities between public transport, crowd mobility, and last mile logistics are scarcely investigated. In this paper, we explore the co-creation of urban mobility services within federated ecosystems focusing on a transshipment hub, and propose a novel approach called “co-bility.” Following a design science research (DSR) approach, we conceptualize a co-bility hub based on literature and expert interviews with practitioners from the mobility sector. The exchange of data and services in urban spaces is based on the technical framework Gaia-X. Our study findings show that a Gaia-X-enabled co-bility hub can be achieved by (a) a federated ecosystem orchestrating mobility services and resources, (b) municipalities ensuring coherent platform governance, and (c) eclectic incentives to make co-bility successful.
  • Conference Paper
    From DevOps to TeachOps: An Agile Approach for Instructional Design
    (Gesellschaft für Informatik e.V., 2023) Göritz, Lorena; Kochon, Enrico; Beinke, Jan Heinrich; Pender, Hanna-Liisa; Thomas, Oliver; Kalenborn, Axel; Fazal-Baqaie, Masud; Linssen, Oliver; Volland, Alexander; Yigitbas, Enes; Engstler, Martin; Bertram, Martin
    The dependence of companies on the education of their employees has positioned human resource development as a strategic asset and a core competitive factor. Instructional design serves a crucial role in optimizing the quality of training and education for sustainable employee qualification. The fast pace of digital transformation demands a new and more agile approach to instructional design, which requires cross-organizational collaboration and the adoption of new frameworks. In response, we propose the TeachOps model, which builds on the principles of DevOps used in software development. The TeachOps model is a new framework for instructional design that enables efficient and continuous HR development. We contribute to the scientific discourse by proposing a new framework that applies DevOps principles to instructional design. Furthermore, we provide practical guidance on how instructional designers can efficiently and continuously provide HR development.
  • Conference Paper
    Projektmanagement und Vorgehensmodelle 2023 - Nachhaltige IT-Projekte - Komplettband
    (Gesellschaft für Informatik e.V., 2023) Bochtler, Stefan; Schomaker, Gunnar; Abbing, Julian; Linssen, Oliver; Behrendt, Till; Sauer, Joachim; Bozaci, Saadet; Lill-Kochems, Lisa; Kalenborn, Axel; François, Peter A.; Kampmann, Marlon; Plattfaut, Ralf; Coners, André; Göritz, Lorena; Kochon, Enrico; Beinke, Jan Heinrich; Pender, Hanna-Liisa; Thomas, Oliver; Greb, Thomas; Guckenbiehl, Pascal; Krieg, Alexander; Brandt, Sarah; Theobald, Sven; Pappert, Laura; Kusanke, Kristina; Randecker, Luca; Engstler, Martin; Heinzel, Viktoria; Vogl, Ulrich; Siegle, Markus; Bacharach, Guido; Jäger, Jakob; Wehnes, Harald; Duschik, Andreas; Goeken, Matthias; Eichenberg, Timm; Peuser, Martina; Hilmer, Stefan; Lieder, Yelle; Jestädt, Martin; Saier, Lena; Siegert, Mara; Yurttas, Aylin; Bitsch, Günter; Koch de Souza, Larissa; Weßel, Christa; Kalenborn, Axel; Fazal-Baqaie, Masud; Linssen, Oliver; Volland, Alexander; Yigitbas, Enes; Engstler, Martin; Bertram, Martin
  • Conference Paper
    Conceptualizing a holistic smart dairy farming system
    (Gesellschaft für Informatik e.V., 2023) Gravemeier, Laura Sophie; Dittmer, Anke; Jakob, Martina; Kümper, Daniel; Thomas, Oliver; Hoffmann, Christa; Stein, Anthony; Ruckelshausen, Arno; Müller, Henning; Steckel, Thilo; Floto, Helga
    With the increasing use of sensor technology and the resulting diverse data streams in dairy farming, the potential for the use of AI rises. Beyond the AI-based solution of individual problems, a holistic approach to smart dairy farming is necessary. In this contribution, we identify and analyse a set of diverse use cases for smart dairy farming: lying behaviour analysis, heat stress monitoring, work diary, barn and herd monitoring, and animal health tracking. These focus both on animal health and welfare as well as assistance for farmers. Based on the requirements of these use cases, we design a holistic smart dairy farming system in an iterative development process.
  • Conference Paper
    Modellierung von Lernprozessen für Augmented-Reality-Brillen in der technischen Aus- und Weiterbildung
    (Gesellschaft für Informatik e.V., 2022) Berg, Matthias; Dreesbach, Tobias; Bonaventura, Katharina; Knopf, Julia; Thomas, Oliver; Henning, Peter A.; Striewe, Michael; Wölfel, Matthias
    Augmented Reality bietet die Möglichkeit interaktive Lernerfahrungen zu schaffen und wird bei Anlernprozessen oder zur Unterstützung situierter Lernszenarien vermehrt eingesetzt. Häufig besteht jedoch nicht die Möglichkeit, auf die Gegebenheiten zugeschnittene Lernprozesse zu erstellen. In diesem Beitrag wird eine Modellierungsumgebung vorgestellt, mit der Lernprozesse digitalisiert und mit Augmented Reality-Lernelementen erweitert werden können.
  • Item
    Innovation by Information Technology Recombination: How Artificial Intelligence Progressive Web Apps Foster Sustainable Development
    (Gesellschaft für Informatik, Bonn, 2021) Fukas, Philipp; Thomas, Oliver
    Artificial Intelligence (AI) and Progressive Web Apps (PWAs) represent two major trends in today’s development of modern information systems. AI aims to automate intelligent behaviour whereas PWAs aim to provide fast, reliable, and engaging applications. The influence of these two key technologies on organisations and sustainable development on their own has already been explored. However, there is no research that merges these technologies in terms of recombinant innovation to show their joint potential. By conducting a systematic literature review this article reveals the positive impact of “Artificial Intelligence Progressive Web Apps” (AI-PWAs) on sustainability. It is shown that AI-PWAs can realise economic, environmental and social benefits and thus can support the achievement of the United Nations’ Sustainable Development Goals.