Publications

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DZHW-Wissenschaftsbefragung 2023. Daten- und Methodenbericht zur DZHW-Wissenschaftsbefragung 2023.

Fabian, G., Heger, C., Just, A., & Weber, A. (2024).
DZHW-Wissenschaftsbefragung 2023. Daten- und Methodenbericht zur DZHW-Wissenschaftsbefragung 2023. Hannover: DZHW. https://doi.org/10.21249/DZHW:scs2023-dmr:1.0.0
Abstract

The DZHW Scientists Survey 2023 is an online survey of full-time academic and artistic staff at German universities and equivalent institutions of higher education with the right to award doctorates. It is repeated at regular intervals as a trend study to explore the working and research conditions at German universities and equivalent institutions of higher education. The DZHW Scientists Survey 2023 was conducted from January to March 2023. The respondents therefore take a retrospective look at their working and research conditions during the Covid-19 pandemic and their current post-pandemic situation. The previous Scientists Surveys took place in 2010, 2016 and 2019/2020. [...] Full Abstract: https://doi.org/10.21249/DZHW:scs2023:1.0.0

Das Zusammenspiel von Methodik und Forschungsethik in der Kommunikations- und Medienforschung.

Zillich, A. F., Schlütz, D., Domahidi, E., & Niemann-Lenz, J. (2024).
Das Zusammenspiel von Methodik und Forschungsethik in der Kommunikations- und Medienforschung. Publizistik, 69(3), 229-235 (online first). https://doi.org/10.1007/s11616-024-00852-9

A mediation strategy for communication between an internal chat system and an open source chat system.

Obionwu, C. V., Kanagaraj, R. R., Kalu, K. O., Broneske, D., Buch, A., Knopke, C., & Saake, G. (2024).
A mediation strategy for communication between an internal chat system and an open source chat system. In Jon-Chao, H. (Hrsg.), New Technology in Education and Training, Select Proceedings of the 5th International Conference on Advance in Education and Information Technology (AEIT 2024) (S. 73-86). Singapore: Springer. https://doi.org/10.1007/978-981-97-3883-0_7

Exploring the predictive factors of heart disease using rare association rule mining.

Darrab, S., Broneske, D., & Saake, G. (2024).
Exploring the predictive factors of heart disease using rare association rule mining. Scientific Reports, 14. https://doi.org/10.1038/s41598-024-69071-6
Abstract

Cardiovascular diseases continue to be the leading cause of mortality worldwide, claiming a significant number of lives each year. Despite the advancements in predictive models, including logistic regression, neural networks, and random forests, these techniques often lack transparency and interpretability, limiting their practical application in clinical settings. To address this challenge, this research introduces EPFHD-RARMING, an innovative approach designed to enhance the understanding and predictability of heart disease through the discovery of rare and meaningful patterns. EPFHD-RARMING utilizes rare association rule mining to [...] Full Abstract: https://www.nature.com/articles/s41598-024-69071-6#citeas

Innovating web probing: Comparing written and oral answers to open-ended probing questions in a smartphone survey.

Lenzner, T., Höhne, J. K., & Gavras, K. (2024).
Innovating web probing: Comparing written and oral answers to open-ended probing questions in a smartphone survey. Journal of Survey Statistics and Methodology (online first). https://doi.org/10.1093/jssam/smae031

Expert agent guided learning with transformers and knowledge graphs.

Obionwu, C. V., Chovatta Valappil, B. B., Genty, M., Jomy, M., Padmanabhan, V., ... & Saake, G. (2024).
Expert agent guided learning with transformers and knowledge graphs. In SciTePress Science and Technology Publications (Hrsg.), Proceedings of the 13th International Conference on Data Science, Technology and Applications (DATA 2024) (S. 180-189). Setúbal, Portugal: Science and Technology Publications.

Examining the link between the ‘middle means typical’ heuristic and answer behavior.

Stefkovics, Á., & Höhne, J. K. (2024).
Examining the link between the ‘middle means typical’ heuristic and answer behavior. Survey Practice (online first). https://doi.org/10.29115/SP-2024-0009

Sharing software-evolution datasets: Practices, challenges, and recommendations.

Broneske, D., Kittan, S., & Krüger, J. (2024).
Sharing software-evolution datasets: Practices, challenges, and recommendations. In Association for Computing Machinery (Hrsg.), Proceedings of the ACM on Software Engineering (S. 2051-2074). New York, NY, United States: ACM. https://doi.org/10.1007/s11616-024-00852-9

Status Quo: Legasthenie oder Dyskalkulie im Tertiärbereich Studium.

Schmidtchen, H. (2024).
Status Quo: Legasthenie oder Dyskalkulie im Tertiärbereich Studium. Wiesbaden: Springer VS. https://doi.org/10.1007/978-3-658-45083-0

Differenzierungen von Arbeitsmarkt- und Bildungserträgen bei Hochqualifizierten. Quantitative Unterschiede zwischen Hochschulabsolvent*innen mit und ohne Promotion.

Euler, T. (2024).
Differenzierungen von Arbeitsmarkt- und Bildungserträgen bei Hochqualifizierten. Quantitative Unterschiede zwischen Hochschulabsolvent*innen mit und ohne Promotion. (Dissertation). Gottfried Wilhelm Leibniz Universität, Hannover. http://dx.doi.org/10.15488/17591

Exploiting shared sub-expression and materialized view reuse for multi-query optimization.

Gurumurthy, B., Bidarkar, V. R., Broneske, D., Pionteck, T., & Saake, G. (2024).
Exploiting shared sub-expression and materialized view reuse for multi-query optimization. Information Systems Frontiers, A Journal of Research and Innovation. https://doi.org/10.1007/s10796-024-10506-w

A design proposal for a unified B-epsilon-tree: Embracing NVM in memory hierarchies.

Karim, S., Wünsche, J., Broneske, D., Kuhn, M., & Saake, G. (2024).
A design proposal for a unified B-epsilon-tree: Embracing NVM in memory hierarchies. In Störl, U. (Hrsg.), GvDB 2024, Grundlagen von Datenbanken 2024, Proceedings of the 35th GI-Workshop Grundlagen von Datenbanken (Herdecke, Germany, May 22-24, 2024) (S. 43-50). Hagen: Fernuniversität Hagen, Databases and Information Systems.

Typing or speaking? Comparing text and voice answers to open questions on sensitive topics in smartphone surveys.

Höhne, J. K., Gavras, K., & Claaßen, J. (2024).
Typing or speaking? Comparing text and voice answers to open questions on sensitive topics in smartphone surveys. Social Science Computer Review (online first). https://doi.org/10.1177/08944393231160961

Nacaps 2018.

Briedis, K., Lietz, A., Ruß, U., Schwabe, U., Seifert, M., ... & Hoffstätter, U. (2024).
Nacaps 2018. Daten- und Methodenbericht zur National Academics Panel Study 2018 (1.-4. Befragungswelle – Promovierende). Hannover: DZHW. https://doi.org/10.21249/DZHW:nac2018:2.0.0
Abstract

Nacaps, the National Academics Panel Study, is a new longitudinal study of doctoral candidates and doctorate holders in Germany funded by the Federal Ministry of Education and Research (BMBF). The project aims at providing nationwide cross-sectional and longitudinal data on doctoral candidates and doctorate holders in Germany regarding their study conditions as well as their career trajectories within and outside of academia. The Nacaps study series apply a panel design to multiple cohorts. Nacaps 2018 is the first cohort in this series of studies. In 2019, all doctoral candidates registered at 53 higher education institutions [...] Full Abstract: https://doi.org/10.21249/DZHW:nac2018:2.0.0

Langzeitarchivierung von Forschungsdaten.

Hoffstätter, U., & Weber, A. (2024).
Langzeitarchivierung von Forschungsdaten. Hannover: DZHW. https://doi.org/10.5281/zenodo.10418834

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