The Project
The project Fully Algorithmic Librarian (FAN) investigates application scenarios of AI-supported methods for research-supporting services – in particular for publication support – in academic libraries in Berlin. The aim is to further develop and publish publication metrics on graphs and to test the application of these findings in libraries. The project is funded as part of the program “Strengthening Innovation Capacities in Information Provision (STiIV)” from 01.11.23 to 31.10.2026.
Organization
The project is carried out by the Cooperative Library Network Berlin-Brandenburg (KOBV), which connects the library landscape of Berlin and Brandenburg and performs important tasks for the member libraries at a central location. KOBV is the only library network in Germany that is affiliated with a research institute. The close proximity to science and research makes it possible to develop and test groundbreaking procedures in information management and to ensure continuous innovation. The KOBV benefits significantly from the Zuse Institute Berlin (ZIB)’s orientation as a research institute for applied mathematics and data-intensive high-performance computing.
Publications and Talks
05.07.2024
05.07.2024
06.06.2024
112. BiblioCon, Hamburg
26.05.2024
26.04.2024
Vu Thi Huong “Discrete Optimal Control With Disturbances: From Coderivative
Theory to Computational Aspects”
12.04.2024
Thorsten Koch “Algorithmic Intelligence: A mostly discrete tour through
challenges in AI Optimization”
30.03.2024
Vu Thi Huong “The Split Feasibility Problem and Beyond”
Workshop on Scientific Computing an Applications, March 27.-30.2024, Hanoi, Vietnam
26.03.2024
Thorsten Koch “Optimal is Next to Illegal: Rules, Objectives, and Computations in Optimization”
Institute of Mathematics, Vietnam Academy of Science and Technology, Hanoi, Vietnam (Invited Talk).
13.12.2023
Thorsten Koch “KI, Kunst und Kultur”
Netzwerk Kultur CDU (online)
Team
Bibliography
„Machine Learning for Scholarly Communication, Libraries and Cultural Heritage“
A curated Zotero bibliography will be continuously updated during the project period and brings together current literature on the topic of machine learning in science communication, libraries and GLAM institutions.