Next Generation Environment for Interoperable Data Analysis - Expert Workshop
Volume, velocity and variety of data has dramatically increased over the last decade, which -- at least in principle -- enables unprecedented and collaborative research. Already today, data volumes are too large to be stored and processed by individual scientists or institutional groups. Moreover the data volume is expected to dramatically increase with the next generation of scientific facilities. This calls for a collaborative strategy and effort from all ErUM communities in order to manage the access to these large amounts of data.
This workshop addresses scientists from *all* ErUM communities in order to obtain a collective understanding on how data are acquired, stored, accessed and analyzed in the different communities. We will focus on existing solutions and real-world experience as well as on the requirements of the individual ErUM communities.
A dedicated session will analyse common requirements and design patterns and discuss strategic synergies for the Next Generation Environment for Interoperable Data Analysis.
The workshop takes place on May 3rd/4th in Berlin, Albert Einstein Str 15, 12489 Berlin (https://indico.desy.de/event/37379/)
- Verena Kain, CERN, “CERN’s control system approach for machine learning for accelerators”
- Mohammad Al Turany, GSI/FAIR: " ALFA: A framework for building distributed applications"
- Kai Polsterer, "Unsupervised ML to explore data: lessons learned from learning machines"
- Niclas Eich, RWTH Aachen, "VISPA: Data Analysis in the Web Browser powered by JupyterLab"
- Community needs
- Data Sources
- Real world experience
- Design Pattern
Scientific organising committee
- Judith Reindl
- Harry Enke
- Kay Graf
- Tim Ruhe
- Pierre Schnizer: