Bern Data Talk: Storing and Sharing Big Data – Workflows and Workarounds

In the field of Big Data, research data management faces particularly complex challenges: How can large data sets be managed, shared, and reused in a resource-efficient way? What solutions exist for sharing large volumes of data within project teams? Can principles such as FAIR Data and Open Research Data be implemented here at all – and if so, how? These and further questions at the intersection of open science, limited resources, and sustainability will be at the heart of the Bern Data Talk in spring 2026. Researchers will share their experiences in addressing these challenges. Join us, exchange ideas – and don’t miss the subsequent apéro for inspiring conversations with speakers and colleagues!   Speakers and Topics

Prof. Dr. Jan Bieser (BFH Wirtschaft) Unpacking the Environmental Impact of Digitalization and AI As digitalization advances and is even further accelerated by AI breakthroughs, the environmental cost of capturing, storing, and processing enormous amounts of data keeps rising. Yet understanding the true scale of these impacts remains a challenge. In this talk, Jan Bieser sheds light on the key drivers behind digital environmental impacts and strategies to mitigate them.   Prof. Dr. Sarah Brüningk (University of Bern, Department of Radiation Oncology) The CAIRO Database – A Foundation for Multimodal Response Modeling in Radiation Oncology We established a scalable, multimodal data infrastructure for radiation oncology research. It integrates sparse, longitudinal data from several sources, including imaging, treatment plans, and clinical tabular data, into a harmonized and analysis-ready  data lake. By combining structured data standards with reproducible processing pipelines, CAIRO transforms heterogeneous routine clinical data into interoperable, research-ready assets to provide faster translational research, smoother multi‑site collaboration and AI development on real‑world clinical data.   Sonia Dupuis MSc (University of Bern, GIUB, Remote Sensing Group) Lessons learned from producing and distributing a multi-decadal satellite archive for the Arctic region The longest satellite data records now span nearly 50 years and are an important source of data for studying the Arctic cryosphere. Deriving consistent physical variables from raw satellite data involves handling data volumes of several hundred terabytes and poses challenges for processing, storage, and data distribution. This talk highlights key lessons learned from building and disseminating a multi-decadal Arctic satellite archive.

When? Tuesday, 21 April, 2026, 4:15 – 5:15 pm, followed by an Apéro for in-depth discussions.

Where? Room 028, University main building, Hochschulstrasse 4