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ESS, MAX IV and SciLifeLab will generate tens of petabytes of data each year through the experiments and measurements performed at the facilities. One petabyte of data is equivalent to approximately 250 billion mobile phone photos or 1 billion books.
This data is the foundation for research breakthroughs in all fields of science – but only if we have strategies for managing, utilizing, quality-assuring, and making it all accessible. A recent study shows that there are significant bottlenecks that need to be addressed for research facilities to fully meet the needs of academia and industry.
At this year's Summit, we will discuss the use of data at facilities and the opportunities AI and machine learning provide.
Welcome to participate on site in Lund or digitally!
Read the report Bottlenecks that slow down the benefits of large-scale research infrastructure
Participate via Youtube
Programme
The program is held in English
Moderator: Maria Borelius
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09:00 Welcome!
Cecilia Sjöberg, Director, Vinnova
Katarina Bjelke, Director General, Swedish Research Council
09:25 - 09:45 Getting data unstuck
Anders Mikkelsen, Professor, Lund University
Filip Lenrick, Senior lecturer, Lund University
Rachid M’saoubi, Senior R&D Expert, SECO Tools
09:45 – 10:10 Our strategies on AI and data
Helmut Schober, Director General, ESS
Olof Karis, Director, MAX IV
Jan Ellenberg, Director, SciLifeLab
10:10 – 10:20 Resources for data sharing, analysis and visualisation
Kajsa M Paulsson, Vice Director, InfraVis
Eva Stensköld, Director, Swedish National Data Service10:20 – 11:00 Coffee and speed dating
11:00 – 12:30 Mini hearing: Handling data from Large-Scale Research Infrastructures
How do research infrastructures like ESS, SciLifeLab and MAX IV meet growing demands for open data, AI integration, and high-quality data management? This session explores how researchers, infrastructure leaders, and funders collaborate to shape the future of data-driven research environments where openness and security go hand in hand.
11:00 – 11:25 Data Sharing Policies and Legislation
This panel focuses on how policy development, legislation, and collaboration between facilities can address the challenges of open, secure, and reusable data—highlighting perspectives from SciLifeLab, ESS, MAX IV, and funding agencies.
Chris Erdmann, Head of Open Science, SciLifeLab
Pascale Deen, Head of the Spectroscopy Division, ESS
Joachim Schnadt, Science Director, MAX IV
Malin Sandström, Senior Research Officer, Swedish Research Council
11:25 – 11:45 Balancing Data Quality vs. Data Quantity
The discussion centres on the tension between generating large volumes of data and ensuring high-quality, usable outputs. What strategies help infrastructures support both high throughput and expert-driven excellence?
Marjolein Thunnissen, Assistant Professor, MAX IV
Henrik Birkedal, Professor, Aarhus University
11:45 – 11:50 Short break
11:50 – 12:10 AI Integration in Data Analysis
This segment looks at how AI can improve the full analysis pipeline—from experimental planning to publication—and what infrastructure developments are needed to support advanced, trustworthy AI applications.
Pablo Villanueva Perez, Associate Professor, Lund University
Alun Ashton, Head of Science IT Infrastructure and Services (AWI) Department, Paul Scherrer Institute
12:10 – 12:30 Community Influence and Data-Centric Approaches
The final panel in this session emphasizes the importance of collaboration between academia, industry, and infrastructures in building sustainable, user-driven ecosystems for data management and AI-enabled analysis.
Magnus Hörnqvist Colliander, Associate professor, Chalmers
Shirin Nouhi, Group Manager, Swerim
Supriya Chitale, Open Source Program Office Manager, IKEA
12:30 – 13:15 Lunch
13:15 – 13:20 The Loop
Daniel Fex, Director Business Development South, Vectura
13:20 – 13:30 LINXS
Trevor Forsyth, Director LINXS
13:30 – 15:00 Mini Hearing: Supporting users with data analysis and visualisation
How can research infrastructures better support users with data-driven analysis, visualization, and AI tools? This session highlights user needs, technological solutions, and organizational models that enable effective and accessible data workflows across academia and industry.
13:30 – 13:50 User Needs in Data Analysis and AI
This panel addresses user needs in data analysis and AI, focusing on how tools and services can be tailored to both academic and industrial users to ensure ease of use and impact.
Ola Spjuth, Professor, Uppsala University
Erik Lindahl, Director, NAISS
Anna Stenstam, CEO, CR
13:50 – 14:10 Data Mining
The discussion explores responsible and reusable data mining practices in both research and industry, and how AI can help uncover new patterns without compromising data integrity.
Phil Ewels, Senior product manager for OSS, Seqera
Eskil Andreasson, Technology Specialist, TetraPak
Fredrik Bolmsten, Group leader Scientific Information Management Systems, ESS
14:10 – 14:20 Short break
14:20 – 14:40 Written Documentation and Data Storage
This panel examines the long-term security of documentation and data storage in a digitized research environment, and the policies and technologies needed to ensure transparency and traceability.
Karin von Wachenfeldt, CEO and co-founder at Truly Labs and Truly Translational
Kostas Tsirigos, Head Research Data Management, DTU Biosustain
14:40 – 15:00 FAIR and Open Data
The concluding segment addresses how FAIR data principles can be implemented in practice, what incentives are needed for metadata sharing, and how collaboration can drive a more open scientific landscape.
Stefan Ekman, Senior Advisor, Swedish National Data Service
Anne Sofie Fink, Head of Data Management, Danish e-infrastructure Consortium
15:00 – 15:30 Coffee and speed dating
15:30 – 16:00 The future of AI and visualisation
Amy Loutfi, Program Director, Wallenberg AI, Autonomous Systems and Software Program
16:10 – 16:30 Action points going forward
Lisbeth Olsson, Secretary General, Research Infrastructures, Swedish Research Council