News

On 13 October 2026, GATE member Anika Müller-Karabil presented the main findings of the GATE Report 2025 at the STOA workshop: Rethinking intellectual property in the era of open science and AI, held at the European Parliament in Brussels, chaired by Lina Gálvez and moderated by Katharina Miller.

STOA (Panel for the Future of Science and Technology) is the European Parliament's in-house think tank providing independent research and analysis on science and technology to support MEPs in their legislative work, thus making it an important stage for community-grounded knowledge like GATE's.

Anika presented GATE's insights into current practices, emerging needs, and persistent capacity building gaps in the Open Science landscape, alongside key recommendations. This work in based on a year of evidence-informed data collection on the state of Open Science - including guiding thoughts and the conceptual foundations drawn from current educational and informational materials and viewed through the lens of the research community itself and concrete solutions to advance Open Science in practice gathered across two solution sessions (Workshop #1 and Workshop #2). 

GATE's topics presented

Although the workshop centred on the implications of Open Science and AI for Intellectual (IP) Property, the GATE data makes one thing clear: these topics are deeply intertwined and deserve a prominent place in policy discussions.

Anika's presentation focused on key topics:
How can we enable the responsible sharing and reuse of research knowledge in an AI-driven research landscape, while ensuring adequate IP protection?

Our findings offer valuable bottom-up insights and highlight several important topics (that are described in the current GATE Report 2025):

1. Responsible research data management is a key priority
The active Open Science community increasingly focuses on responsible data management practices, tools and infrastructures. These form a fundamental foundation for the reliable and responsible integration of AI into research.

2. AI is seen not only as a challenge, but also as an enabler of Open Science
Rather than perceiving AI solely as a potential threat to research and IP, researchers also recognise its potential to facilitate Open Science and the reuse of research knowledge. Examples include supporting metadata creation and generating synthetic data that can be used in research processes instead of sensitive data. Such practices can contribute to protecting IP while significantly facilitating the sharing and reuse of research outputs. Looking ahead, AI-assisted metadata annotation — potentially including licence information by default — could help enable IP-aware data management and support responsible human- and machine-based reuse of research data, including AI processing.

3. IP protection remains insufficiently visible in Open Science discussions
IP protection is still not consistently addressed as a central element of the broader Open Science capacities. However, it tends to receive greater attention when discussions explicitly turn to the potential applications and implications of AI.

4. Open Science capacity-building needs to move beyond concepts towards practical implementation
Existing educational and informational resources effectively communicate key principles, such as “as open as possible, as closed as necessary,” the FAIR principles and reliability. However, practical instruments and approaches for implementing these principles — including data protection and traceability — receive comparatively less attention.

What GATE recommends: Closing this capacity-building gap is essential
These findings reinforce GATE’s call to strengthen capacity-building by integrating knowledge about practical tools and methods for implementing Open Science more systematically into educational and informing capacities, while supporting the research community in developing and accessing the tools and infrastructures it needs.