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Dr Andreas Knüpfer (Technische Universität Dresden)29/09/2022, 13:10
TU Dresden aims to improve its services for Research Data Management (RDM) supporting scientists even better with managing their valuable data. Among the challenges are handling large data sets, keeping track of one/many data sets across various storage technologies and storage tiers including many versions of datasets over their lifetimes. As part of the challenge there is metadata to be...
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Hendrik Nolte (GWDG)29/09/2022, 13:40
Across various domains, data lakes are successfully utilized to centrally store all data of an organization in their raw format. This promises a high reusability of the stored data since a schema is implied on read, which prevents an information loss due to ETL (Extract, Transform, Load) processes. Despite this schema-on-read approach, some modeling is mandatory to ensure proper data...
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Dr Ilona Lang (RWTH Aachen University)29/09/2022, 14:10
For many researchers an involvement with the FAIR principles (finable, accessible, interoperable, reusable) does not begin until the publication of an article and the sometimes obligatory transfer of the research data to a repository. At this point, a significant amount of valuable information about the research project is often already lost. One solution to make research data FAIR from the...
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Dr Steffen Christgau (Zuse Institut Berlin)29/09/2022, 15:00
The Distributed Asynchronous Object Storage (DAOS) is a new and pure user-space HPC storage software solution developed by Intel. It is built upon recent hardware technologies and while being a key-value store it breaks with traditional POSIX-like HPC file systems. Despite the discontinuation of Optane persistent memory, a key technology DAOS currently relies on, the development on the...
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Christian Köhler (GWDG)29/09/2022, 15:30
The usual mode of accessing High Performance Computing (HPC) resources involves interactively connecting to the command-line interface and submitting job scripts to a job scheduler. However, some services which provide a user interface by themselves (e.g. when working with graphical data) or services which simply require HPC resources as a backend compute engine, can benefit from the...
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Mr Trevor Khwam Tabougua (GWDG)29/09/2022, 16:00
Driven by the progress of data and compute-intensive methods in various scientific domains, there is an increasing demand from researchers working with highly sensitive data to have access to the necessary computational resources to be able to adapt those methods in their respective fields. To satisfy the computing needs of those researchers cost-effectively, it is an open quest to integrate...
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