RepositoryPlease use this identifier to cite or link to this item:
http://hdl.handle.net/11366/2569| Title: | The power of generative AI for CRIS systems: a new paradigm for scientific information management | Authors: | Guillaumet, Anna Andrés, Aurelia |
Keywords: | research information management;current research information management;artificial intelligence;generative AI | Issue Date: | 16-May-2024 | Publisher: | euroCRIS | Series/Report no.: | CRIS2024: 16th International Conference on Current Research Information Systems (Vienna, Austria, May 15-17, 2024) | Conference: | CRIS2024 – Vienna | Abstract: | This paper presents a comprehensive analysis of potential generative AI applications within CRIS systems, identifying key benefits such as improved data quality, advanced analysis and visualization capabilities, and enhanced decision-making support. However, the integration of AI also introduces challenges, including data quality assurance, architectural requirements, ethical considerations, and the need for transparency and trust in AI-generated outcomes. |
Description: | Extended abstract presented at the CRIS2024 conference in Vienna.-- Event programme available at https://cris2024.eurocris.org/#programme 32 slides.-- Presentation delivered within Session 5.1 "Artificial Intelligence" on Thu May 16th, 2024 |
URI: | http://hdl.handle.net/11366/2569 | DOI: | 10.1016/j.procs.2024.11.057 |
| Appears in Collections: | Conference |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Guillaumet-Andrés_CRIS2024_The-power-of-generative-AI-for-CRIS-systems.pdf | Extended abstract (PDF) | 269.36 kB | Adobe PDF | View/Open |
| Guillaumet-Andrés_CRIS2024_slides_The-power-of-generative-AI-for-CRIS-systems.pdf | Presentation (PDF) | 2.61 MB | Adobe PDF | View/Open |
Page view(s)
240
checked on Apr 16, 2025
Download(s)
272
checked on Apr 16, 2025
Google ScholarTM
Check
Altmetric
Items in DSpace are offered under a CC-BY 4.0 licence unless otherwise indicated