
This report summarises the process and outcomes of Open Science Learning GATE's (GATE) Solution Session at the Open Science Conference 2025, hosted by Leibniz Strategy Forum Open Science and organised under the lead of the ZBW – Leibniz Information Centre for Economics. s an annual event that brings together diverse stakeholders and key actors in the field of Open Science (OS) to exchange ideas on current and emerging trends aimed at advancing OS. This year’s event took place from October 8 to 9 in Hamburg and focused on OS in the era of AI, highlighting both the challenges and opportunities shaping this intersection. The GATE Solution Session brought together participants from the fields of research, education, data management, library, software development, AI consultation, (OS) science management, scholarly communication, policymaking and law to explore the intersection of Open Science and Artificial Intelligence and to co-create concrete actions supporting Open Science development and implementation, including its intersection with Artificial Intelligence. Drawing on data and material from the GATE, participants designed tailored solutions for their communities and discussed ways to strengthen capacity building in the age of Artificial Intelligence.
Solution Session, Workshop
Solution Session, Workshop
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
