MessageID: 201812101550 Time: 13.12.2018, 5:00 p.m. to 6:30 p.m. Affected: Trouble Ticket System OTRS Impact: ticket processing delayed, OTRS web interface unaccessable

On 13.12.2018 between 5:00 p.m. and approx. 6:30 p.m. the GWDG trouble ticket system OTRS will be under maintenance. While it still will be possible to send requests as usual to our service hotline at support@gwdg.de , no automatic responses or ticket processing will take place, so some delays may be expected. Additionally the OTRS web interface More….

For the third year in a row, the eResearch Alliance is offering an International Summer School on Data Science in 2019. Here young scholars can learn what insights Data Science offers for their specific research project. Application is open now until 22 January 2019.

Data Science is quickly emerging as an indispensable tool for scientific work and research. Young researchers can greatly benefit from learning what the field of Data Science encompasses, how Data Science can be applied to scientific inquiries, and what skill-set a data scientist should hope to acquire in a world deluged by data.

The November issue of the GWDG News has just been published.

It contains among others the following topics:

• GWDG´s Samba Service
• Meeting of the Institute Administrators
• The DFG Project “GFBio“ – a Central Point of Contact for the Management of Research Data in the Biolology and Environmental Science

>> Click here for the GWDG News 11/2018

The GWDG course program for 2019 has been published. It again offers a wide range of courses for efficient use of hardware, software and networks.

If you have requests for other courses that are not included in the current course program, please send an e-mail to support@gwdg.de .

More information …

GWDG now provides a Jupyter-Hub instance that is connected to the GWDG Scientific Compute Cluster. This instance provides two usage modes:

1.) Standard mode: This usage mode is useful, if your Jupyter notebooks are too resource demanding for our standard Jupyter-Hub instance or require access to large data sets.

2.) Parallel mode: You can use parallelization with IPython Parallel in your notebooks and make use of large numbers of nodes for truly demanding workflows.

More….