Volume, velocity and variety of data has dramatically increased over the last decade, which make these data precious and -- at least in principle -- enables unprecedented collaborative research. Already today, data volumes are too large to be stored and processed by individual scientists or instutional 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 analysis and access to these large amounts of data.
Building on the insights and experiences from our previous workshop, this event addresses scientists from all ErUM communities. Our goal is formulate a common strategy on how to manage and maintain the access to data and workflows provided by the different stakeholders, ranging from large international collaborations to individual scientists. The common strategy will also discuss requirements with respect to infrastructure and research data management with a focus on the user facing components.
Main focus:
- work flow engines
- large language models
Keynote Speakers
- Arman Khalatyan (AIP)
- Harry Enke (AIP)
- Jan Lucas Uslu (RWTH Aachen)
- Thomas Kuhr (LMU)
- Tibor Simko (CERN)
Please bring a laptop with you for participating in the hands on tutorial. Details are given in the Tutorial
This workshop builds on the previous expert workshop Next Generation Environment for Interoperable Data Analysis (https://indico.desy.de/event/37379/).
This is Workshop is organized by the DIG-UM Topic Group User Interface with support of the ErUM-Data-Hub.
This workshop is addressed to scientists from all ErUM communities.
A fee of 50€ will be charged for participation in the workshop.
