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
Programme
The program is held in English
Moderator: Maria Borelius
9.00 Welcome!
Darja Isaksson, director general, Vinnova
Katarina Bjelke, director general, Swedish Research Council
9.25–9.45 Unloading data
Anders Mikkelsen, professor, Lund University
Filip Lenrick, senior lecturer, Lund University
Rachid M’saoubi, senior expert in research and development, SECO Tools
9.45–10.10 Our strategies for 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 visualization
Kajsa M Paulsson, Deputy director, InfraVis
Eva Stensköld, director, National Data Service
10.20–11.00 Coffee and speed dating
11.00–12.30 Mini-hearing: Management of data from large-scale research infrastructures
How are research infrastructures like ESS, SciLifeLab, and MAX IV meeting growing eligibility requirements for open data, AI integration, and high-quality data management? This session explores how researchers, infrastructure leaders, and funders are collaborating 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 – and highlights perspectives from SciLifeLab, ESS, MAX IV, and funding agencies.
Chris Erdmann, Head of Open Science, SciLifeLab G
iovanna Fragneto, Head of Science, ESS
Joachim Schnadt, Chief Scientific Officer, MAX IV
Malin Sandström, Senior Researcher, Swedish Research Council
11.25–11.45 Balance between data quality and data quantity
The discussion focuses on the tension between generating large amounts of data and ensuring high-quality, usable results. What strategies help infrastructures support both high throughput and expert-driven excellence?
Marjolein Thunnissen, Assistent Professor, MAX IV
Henrik Birkedal, Professor, Aarhus Universitet
11.45–11.50 Short break
11.50–12.10 AI integration in data analysis
This segment looks at how AI can improve the entire analysis process – from experimental planning to publication – and what infrastructure developments are needed to support advanced, reliable AI applications.
Andy Götz, ESRF Data Manager and PaNOSC Coordinator (TBC)
Pablo Villanueva Perez, Associate Professor, Lunds Universitet
12.10–12.30 Social influence and data-centric approaches
The final panel in this session emphasizes the importance of collaboration between academia, industry, and infrastructure to build sustainable, user-driven ecosystems for data management and AI-enabled analytics.
Magnus Hörnqvist Colliander, Associate Professor, Chalmers
Shirin Nouhi, Group Manager, Swerim
Supriya Chitale, Open Source Program Manager, IKEA 1
2.30–1.15 pm Lunch
13.15–13.20 The Loop Daniel Fex, Director of Business Development South, Vectura
13.20–13.30 LINXS
Trevor Forsyth, Director LINXS
13.30–15.00 Mini-hearing: Supporting users with data analytics and visualization How can research infrastructures better support users with data-driven analytics, visualization and AI tools? This session highlights user needs, technical solutions and organizational models that enable efficient and accessible data workflows in academia and industry.
13.30–13.50 User needs in data analysis and AI Denna panel addresses user needs in data analysis and AI, focusing on how tools and services can be tailored for both academic and industrial users to ensure user-friendliness 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 methods 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
Thomas Holm Rod, Head of DMSC, 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 of Truly Labs and Truly Translational
Theodora Kontogianni, Assistant Professor, Danmarks Tekniska Universitet (TBC)
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.
Frida Bender, member of the NAISS steering committee and associate professor, Stockholm University (TBC)
Paul Millar, expert in scientific data management, DESY (TBC)
15.00–15.30 Coffee and speed dating
15.30–16.00 The future of AI and visualization
Amy Loufti, Program Manager, Wallenberg AI, Autonomous Systems and Software Programs
16.10–16.30 Future measures
Katarina Bjelke, director general, Svenska Forskningsbolaget