Organisation von Wissen. Zwischen Offenheit und Exklusivität
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Dieser Forschungsschwerpunkt beschäftigt sich mit Fragen zur Arbeitswelt, dem Bildungssystem und der Wissenschaft. Vor allem: Wie offen bzw. exklusiv werden Daten und Wissen hier verarbeitet und organisiert? Dabei wird auf Perspektiven aus der Informatik, Wirtschaftsinformatik, Soziologie und Innovationsforschung zurückgegriffen.
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- ItemBetween geoeconomic competition and local embeddedness - how Chinese investors influence digitalisation in acquired German manufacturing companies(Inderscience Publishers, 2025) Schneidemesser, LeaThe growing economic and geopolitical importance of digital technologies and data, coupled with the Chinese Government’s expressed ambition for Chinese companies to occupy a leading position in this domain, raises questions regarding the role of acquired foreign subsidiaries in realising this objective. Drawing on comparative capitalism research, this paper discusses how local institutions, investor strategies, and the aspirations of the Chinese Government interact to shape the digital transformation of manufacturing companies in Germany. It empirically investigates how digitalisation is unfolding in 15 German manufacturing companies with Chinese investors and enhances the understanding of the influence of Chinese MNCs on company-level digitalisation abroad. The eight companies that undertake digitalisation projects show that the German companies mainly control the digitalisation of processes while Chinese parent companies and subsidiaries in China play a key role in developing digital business models. This signals a shift in innovation patterns and changes in inter-firm relationships.
- ItemGekommen, um zu bleiben? Dauerstellenkonzepte an Universitäten in Deutschland(2025) Bloch, Roland; Krüger, Anne K.; Würmann, CarstenSeit einigen Jahren wird verstärkt die Erwartung an Universitäten in Deutschland gerichtet, dauerhafte Karriere- und Beschäftigungsperspektiven jenseits der Professur zu schaffen. Bislang liegen aber kaum Erkenntnisse darüber vor, welche Aktivitäten Universitäten verfolgen, um diese Erwartung zu erfüllen. Der Beitrag adressiert auf Grundlage einer explorativen Studie von Dauerstellenkonzepten an Universitäten in Deutschland diese Lücke. Dargestellt wird, wie Universitäten diese Forderungen aus der öffentlichen Diskussion aufgreifen, welche Dauerstellenkonzepte sie entwickeln, welche Überlegungen dahinterstehen und vor welche Herausforderungen und Probleme sie dabei gestellt sind. , For some years now, universities in Germany have been increasingly expected to establish long-term career and employment prospects beyond the professorship. To date, however, little is known about the activities universities are pursuing to fulfill this expectation. This article addresses this gap on the basis of an exploratory study of concepts for permanent positions at universities in Germany. It shows how universities take up these demands from the public debate, which concepts for permanent positions they develop, the considerations behind them, and the challenges and problems they face in doing so.
- ItemBehind the Screens: How Algorithmic Imaginaries Shape Science Content on Social Media(SISSA Medialab srl, 2025) Walter, Clarissa Elisa; Friesike, SaschaBased on an ethnography of the development and production of science YouTube videos – a collaboration between a German public broadcaster and social science scholars – we identify three intermediary steps through which recommendation algorithms shape science content on social media. We argue that algorithms induce
- ItemExploring Prompt Generation Utilizing Graph Search Algorithms for Ontology Matching(IOS Press, 2024) Sampels, Julian; Efeoglu, Sefika; Schimmler, Sonja; Salatino, Angelo; Alam, Mehwish; Ongenae, Femke; Vahdati, Sahar; Gentile, Anna-Lisa; Pellegrini, Tassilo; Jiang, ShufanThe interoperability of domain ontologies, developed by domain experts, necessitates their alignment before attempting to match them. Within these ontologies, defined concepts often encounter an ambiguity problem stemming from the use of natural language. This interoperability issue raises the underlying ontology matching (OM) challenge. OM might be defined as the identification of correspondences or relationships between two or more entities, such as classes or properties among two or more ontologies. Rule-based ontology matching approaches, e.g., LogMap and AML have not outperformed machine learning based matchers on the Ontology Alignment Evaluation Initiative (OAEI) benchmark datasets, especially on the OAEI Conference track since 2020. Supervised machine or deep learning approaches produce the best results but require labeled training datasets. In the era of Large Language Models (LLMs), robust zero-shot prompting of LLMs can also return convincing responses. While prompt generation requires prompt template engineering by domain experts, contextual information about the concepts to be aligned can be retrieved by leveraging graph search algorithms. In this work, we explore how graph search algorithms, namely (i) Random Walk and (ii) Tree Traversal can be utilized to retrieve the contextual information to be incorporated into prompt templates. Through these algorithms, our approach refrains from considering all triples connected with a concept to be aligned in its contextual information creation. Our experiments show that including the retrieved contextual information in prompt templates improves the matcher’s performance. Additionally, our approach outperforms previous works leveraging zero-shot prompting.
- ItemUncertain futures of work: The perception of generative AI in knowledge professions(Nomos, 2025) Butollo, Florian; Haase, Jennifer; Katzinski, Ann-Kathrin; Krüger, Anne K.; Kox, Thomas; Ullrich, André; Zech, HerbertThe application of generative AI (GenAI) tools has led to widespread speculation about the implications of technological change for the future of cognitive work. This article provides insights on how the use of GenAI affects work practices in the fields of IT programming, science and coaching based on expert interviews and a quantitative survey among users of GenAI. Specifically, we ask about perceptions on skills, creativity, and authenticity, which we regard as key qualities of cognitive work. Contrary to widespread expectations that AI use would hollow out or substitute aspects of cognitive work, we find that there is a strong awareness for the meaning of the professional core in each field. We conclude that the use of AI provokes reflections about the meaning of human work in operating AI tools adequately and taking on responsibility for their results, thereby rather reinforcing its relevance.