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Can generative AI transform data quality? A critical discussion of ChatGPT’s capabilities.

Azeroual, O. (2024).
Can generative AI transform data quality? A critical discussion of ChatGPT’s capabilities. Academia Engineering, 2024(4). https://doi.org/10.20935/AcadEng7407

Security of AI-Powered Systems: Threat Intelligence on the Edge.

Nacheva, R., & Azeroual, O. (2024).
Security of AI-Powered Systems: Threat Intelligence on the Edge. In Yaşar, E. et al. (Hrsg.), 8th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 07-09 November 2024. (S. 1-6). Ankara, Turkiye: IEEE.

Smart Data Stewardship: Innovating Governance and Quality with AI.

Azeroual, O. (2024).
Smart Data Stewardship: Innovating Governance and Quality with AI. In L. Gruenwald, E. Masciari, & J. Bernardino (Hrsg.), Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (S. 187-196). Porto, Portugal: SciTePress - Science and Technology Publications, Lda.. https://doi.org/10.5220/0012918200003838

" Dear Colleague " : Effects of Personalization in Survey Invitations to Scientists in Germany.

Heger, C., & Ambrasat, J. (2024).
"Dear Colleague": Effects of Personalization in Survey Invitations to Scientists in Germany. Web: SocArxiv.

From Open Repositories to CRIS - A Case Study.

Schöpfel, J., Azeroual, O., Chaudiron, S., Jacquemin, B., Kergosien, E., Prost, H., & Thiault, F. (2024).
From Open Repositories to CRIS - A Case Study. Procedia Computer Science, 2024(249), 173-178. https://doi.org/10.1016/j.procs.2024.11.061

Bridging the evidence use gap between higher education research and science studies, policy and practice – Notions and functions of intermediaries.

Wegner, A. (2024).
Bridging the evidence use gap between higher education research and science studies, policy and practice – Notions and functions of intermediaries. In STI2024 (Hrsg.), Proceedings of the 28th International Conference on Science, Technology and Innovation Indicators (STI2024). Berlin: Zenodo.

Knowledge Graphs – The Future of Integration in CRIS Systems for Uses of Assistance to Scientific Reasoning.

Fabre, R., & Azeroual, O. (2024).
Knowledge Graphs – The Future of Integration in CRIS Systems for Uses of Assistance to Scientific Reasoning. Procedia Computer Science, 2024(249), 264-279. https://doi.org/10.1016/j.procs.2024.11.072

Ethical aspects using AI in CRIS.

Azeroual, O., Schöpfel, J., Störl, U., & Maru¨ić, A. (2024).
Ethical aspects using AI in CRIS. Procedia Computer Science, 2024(249), 150-159. https://doi.org/10.1016/j.procs.2024.11.058

Gender bias in grant allocation shows a decline over time.

van den Besselaar, P., Möller, T., Mom, C., Cruz-Castro, L., & Cruz-Castro, L. (2024).
Gender bias in grant allocation shows a decline over time. In STI 2024 (Hrsg.), Proceedings of the 28th International Conference on Science, Technology and Innovation Indicators (STI2024). Berlin: STI2024. https://doi.org/10.5281/zenodo.14176637

Are there factors that influence the quality of funding acknowledgements in publications?

Möller, T., Scheidt, B., & Meier, A. (2024).
Are there factors that influence the quality of funding acknowledgements in publications? In STI2024 (Hrsg.), Proceedings of the 28th International Conference on Science, Technology and Innovation Indicators (STI2024). Berlin: STI2024. https://doi.org/10.5281/zenodo.14174157

Is academic freedom associated with strong science?

Lovakov, A. (2024).
Is academic freedom associated with strong science? In STI2024 (Hrsg.), Proceedings of the 28th International Conference on Science, Technology and Innovation Indicators (STI2024). Berlin: STI2024. https://doi.org/10.5281/zenodo.14168639

Funding decision and applicants' careers. A case study of an early career grant.

Möller, T. (2024).
Funding decision and applicants' careers. A case study of an early career grant. In STI2024 (Hrsg.), Proceedings of the 28th International Conference on Science, Technology and Innovation Indicators (STI2024). Berlin: STI2024. https://doi.org/10.5281/zenodo.14171970

Ergebnisse der Trendumfrage Forschungsdateninfrastrukturen 2024.

Hartstein, J., & Blümel, C. (2024).
Ergebnisse der Trendumfrage Forschungsdateninfrastrukturen 2024. Hannover: Zenodo. https://doi.org/10.5281/zenodo.14093010
Abstract

Die Trendumfrage FDI 2024 ist Teil der Begleitforschung zu den NFDI-Basisdiensten (Base4NFDI). Wir betrachten in der vorliegenden Umfrage Wahrnehmung, Nutzung und Bewertung bestehender und neuer Dateninfrastukturen und Dienste in der deutschen Forschungslandschaft. Die Trendumfrage adressiert die Perspektive der (potentiellen) Nutzenden.

Data inaccuracy quantification and uncertainty propagation for bibliometric indicators.

Donner, P. (2024).
Data inaccuracy quantification and uncertainty propagation for bibliometric indicators. Research Evaluation, 33. https://doi.org/10.1093/reseval/rvae047
Abstract

This study introduces an approach to estimate the uncertainty in bibliometric indicator values that is caused by data errors. This approach utilizes Bayesian regression models, estimated from empirical data samples, which are used to predict error-free data. Through direct Monte Carlo simulation—drawing many replicates of predicted data from the estimated regression models for the same input data—probability distributions for indicator values can be obtained which provide the information on their uncertainty due to data errors. [...]

Evidence use in higher education decision-making and policy: a scoping review of empirical studies from 2010 to 2022.

Thiedig, C., & Wegner, A. (2024).
Evidence use in higher education decision-making and policy: a scoping review of empirical studies from 2010 to 2022. London Review of Education, 22(1). https://doi.org/10.14324/LRE.22.1.36

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