Welcome
Klaus Tochtermann,

ZBW – Leibniz Information Centre for Economics

Keynote
FAIR and verifiable: The role of FAIR Digital Objects in trusted AI
Erik Schultes, Leiden University

The many digital objects that are created or used by researchers throughout the Research Lifecycle are largely not FAIR. The resulting lack of provenance leads to fragmentation and loss of the scientific record, inefficient research programming and opaque academic publishing. In the Leiden academic community, we are experimenting with the use FAIR Digital Objects as FAIR and verified “metadata tags” to track the digital assets composing the Research Lifecycle (data, software and methods among them). Erik will report findings from these pilots and prospects for broader application in Leiden and beyond. Research data and metadata that adhere to the FAIR Principles enhance the ability of machines to Find, Access, Interoperate with and Reuse data making AI more trustworthy, equitable, and fit to purpose. This opens the door to virtuous feedback loops where FAIR data engenders trusty AI that is increasingly entrusted with the creation of FAIR data.  

10:30

Break

Break

Networking

12:30 – 13:30: Poster & demo session (corridor in front of the room “Galeria”)
list of posters /demos

14:30

Break

Break

19:00

Conference Dinner

Conference Dinner

Welcome
Michela Vignoli, AIT Austrian Institute of Technology

Keynote
Data Infrastructures and Data Competencies as a Foundation for AI Projects
Sonja Schimmler, TU Berlin / Fraunhofer FOKUS

This presentation will examine the critical components that drive AI progress, with a focus on the need for large-scale, machine-interpretable data that adapts to the unique demands of different sectors. Key topics will include transparency and reproducibility in AI projects, as well as the importance of making essential resources—publications, data, models, and code—available and interconnected.

Robust data infrastructures and profound data competencies are important for the AI community, supporting every stage of the data lifecycle—from collection and creation to processing, analysis, publishing, archiving, and reuse of resources. This talk will highlight the foundational role of infrastructures and competencies in AI-driven initiatives, showcasing several ongoing initiatives and illustrating how they contribute to a modern research environment.

10:30

Break

Break

Networking

12:30 – 13:30: Poster & demo session (corridor in front of the room “Galeria”)
list of posters /demos

14:30

Break

Break

Discussion Session / Panel discussion

The role of Open Science in safeguarding the research enterprise

Openness and transparency is fundamental to driving innovation, inclusion, and accountability in research. Simultaneously, there are considerations, such as security, economic interests, influence, and interference of research, that must be mitigated across a spectrum of risk and that needs to be adaptable to changing trends, such as the rapid growth of artificial intelligence and changing political interests.

This discussion session will start with 5 minute impulse statements from each of the panelists before shifting to a moderated discussion with the audience and panelists centered around the following guiding questions:

1. How does open science make science more resilient to external influences?;
2. How does open data and open access contribute to the credibility of research?
3. How can open processes, like preregistration and open peer review, protect against influence and interference?
4. What strategies can be used to balance open science principles with the need to protect sensitive information, such as security and intellectual property?

Panellists

• Peter Suber, Harvard Library / Harvard Open Access Project (online)
• Jez Cope, The British Library
• Julia Prieß-Buchheit, Kiel University

Moderation: Tim Errington, Center of Open Science