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Platformization of Scholarly Communication: Academic Social Networking Sites as New Infrastructures and Organizations. Köchling, S. (2025). Platformization of Scholarly Communication: Academic Social Networking Sites as New Infrastructures and Organizations. Emerging Media: Technology, Industry and Society. 10.1177/27523543251346565 (Abgerufen am: 02.06.2025) (online first).
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Embracing NVM: Optimizing $B^𝜖$-tree structures and data compression in storage engines. Karim, S., Wünsche, F., Broneske, D., Kuhn, M., & Saake, G. (2025). Embracing NVM: Optimizing $B^𝜖$-tree structures and data compression in storage engines. In Binnig, C. et al. (Hrsg.), Datenbanksysteme für Business, Technologie und Web - Workshopband (BTW 2025) (S. 329-333). Bonn: Gesellschaft für Informatik. https://doi.org/10.18420/BTW2025-137
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Erste unter Gleichen. Donner, P. (2025). Erste unter Gleichen. Forschung und Lehre (online first).
Abstract
Bei Artikeln in Ko-Autorschaft wird oft um die Autorenreihenfolge gerungen. Einige (ungewöhnliche) Lösungsvorschläge im Überblick.
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Public participation and transparency: Does open governance promote inclusion and accountability? Cruz Romero, R. (2025). Public participation and transparency: Does open governance promote inclusion and accountability? JeDEM - eJournal of eDemocracy and Open Government, 17(2), 31-64. https://doi.org/10.29379/jedem.v17i2.963
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Publishing fine-grained standardized metadata – Lessons learned from three research data centers. Wenzig, K., Daniel, A., Hansen, D., Koberg, T., & Tudose, M. (2025). Publishing fine-grained standardized metadata – Lessons learned from three research data centers. 2025 (12). Berlin: Konsortium für die Sozial-, Verhaltens-, Bildungs- und Wirtschaftswissenschaften (KonsortSWD).
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A multi-objective evolutionary algorithm for detecting protein complexes in PPI networks using gene ontology. Abbas, M. N., Broneske, D., & Saake, G. (2025). A multi-objective evolutionary algorithm for detecting protein complexes in PPI networks using gene ontology. Scientific Reports, 15. https://doi.org/10.1038/s41598-025-01667-y
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Transparency in open science: An actionable principle? Cruz Romero, R. (2025). Transparency in open science: An actionable principle? Open Information Science, 9(1), 1-15. https://doi.org/10.1515/opis-2025-0016
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Honorierung von Leitlinienarbeit: die Perspektive der Engagierten. In der Smitten, S., Aman, V., Sorgatz, N., Traylor, C., & Herrmann-Lingen, C. (2025). Honorierung von Leitlinienarbeit: die Perspektive der Engagierten. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen (online first). https://doi.org/10.1016/j.zefq.2025.04.004
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The impact of the Covid-19 pandemic on social inequalities in international student mobility: A scoping review. Almeida, J., Netz, N., Nika, D., Krzaklewska, E., Aguiar, J., ... & Malet Calvo, D. (2025). The impact of the Covid-19 pandemic on social inequalities in international student mobility: A scoping review. Comparative Migration Studies, 13(1), 27. https://doi.org/10.1186/s40878-025-00436-0
Abstract
This systematic literature review sheds light on social inequalities in students’ access to and experiences of international student mobility (ISM) in the context of the Covid-19 pandemic. Following a scoping approach based on the 2020 PRISMA guidelines, it synthesises 48 empirical studies published in the most intense phase of the Covid-19 pandemic, namely between January 2020 and June 2022.
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Revolutionary synergy: The fusion of data mesh and data fabric for strategy analytics in GRAPHYP knowledge graph. Azeroual, O., Fabre, R., & Störl, U. (2025). Revolutionary synergy: The fusion of data mesh and data fabric for strategy analytics in GRAPHYP knowledge graph. In Coenen, F. et al. (Hrsg.), Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2023. Communications in Computer and Information Science (S. 277-295). Cham: Springer. https://doi.org/10.1007/978-3-031-87569-4_13
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AutoML meets hugging face: Domain-aware pretrained model selection for text classification. Safikhani, P., & Broneske, D. (2025). AutoML meets hugging face: Domain-aware pretrained model selection for text classification. In A. Ebrahimi, S. Haider, E. Liu, M. L. Pacheco, & S. Wein (Hrsg.), Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop). Albuquerque, USA: Association for Computational Linguistics.
Abstract
The effectiveness of embedding methods is crucial for optimizing text classification performance in Automated Machine Learning (AutoML). However, selecting the most suitable pre-trained model for a given task remains challenging. This study introduces the Corpus-Driven Domain Mapping (CDDM) pipeline, which utilizes a domain-annotated corpus of pre-fine-tuned models from the Hugging Face Model Hub to improve model selection. Integrating these models into AutoML systems significantly boosts classification performance across multiple datasets compared to baseline methods. Despite some domain recognition inaccuracies, results demonstrate CDDM’s potential to enhance model selection, streamline AutoML workflows, and reduce computational costs.
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How Does Taking Parental Leave Affect the Wages of Highly Educated Parents? Jaksztat, S., Goldan, L., & Gross, C. &. (2025). How Does Taking Parental Leave Affect the Wages of Highly Educated Parents? Journal of Marriage and Family (online first). https://doi.org/10.1111/jomf.13109
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Inequality at the Transition to Higher Education in Germany: Social Differences by Prior Educational Pathways. Quast, H., Spangenberg, H., Mentges, H., Ordemann, J., & Buchholz, S. (2025). Inequality at the Transition to Higher Education in Germany: Social Differences by Prior Educational Pathways. Social Inclusion, 2025(13). https://doi.org/10.17645/si.8766
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A CRISP-DM and predictive analytics framework for enhanced decision-making in research information management systems. Azeroual, O., Nacheva, R., Nikiforova, A., & Störl, U. (2025). A CRISP-DM and predictive analytics framework for enhanced decision-making in research information management systems. Informatica, 2025(49), 67-86. https://doi.org/10.31449/inf.v49i18.5613
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