Page History

In this seminar we will introduce the AWI's Albedo HPC System. The computer's hardware will be introduced along with a beginner introduction to using the machine, including recommended storage locations, available software, and usage of the batch system for scheduling your computations

Digital data Acquisition–Mobile Apps and Tools for Data acquisition:

• Voice recognizing data aquisition
• How to document events in the field (Mobile Event Log)
• Citizen science app based (MyThaw)

Data Logistics Support group (DLS):

• Norbert Anselm
• Maximilian Betz
• Janik Eilers
• Sebastian Immoor
• Rebecca Lauerburg

Unlocking the potential of ML for Earth and Environment researchers

Abstract:

As Helmholtz AI Consultants, we support Helmholtz-based researchers on making the best use of ML methods for research questions related to Earth and Environmental sciences. This talk will introduce you to the way we work and what we have on offer for you. We will give insights into typical problem statements from Earth observation and Earth System modelling that are good candidates for experimentation with ML methods and report on our accumulated experience tackling such challenges with individual support projects. Given sufficient amounts of data and initial scientific problem statements, we work towards assembling practically meaningful demonstrators within a couple of months, laying the groundwork for further research projects. Example projects include wind speed regression on GNSS-R data, emulation of atmospheric chemistry modeling, Earth System model parameterizations with ML, marine remote sensing and time series analysis. We are happy to share our experiences and discuss the development of ML methods, prototypes and projects based on your input and scientific needs.

General Introduction (15 min)

• Data submission as part of Research Data Management
• GFBio’s single point of entry for submitting data to ENA & PANGAEA
• NFDI4Biodiversity as a sustainability concept

Introduction to MIxS (15 min)

• What is MIxS
• Packages available
• Examples 
• ENVO - the Environment Ontology
• MIxS and ENVO together

Demo (30 min)

• Submission template for sequence data
• Available fields (default fields and suggested for FAIRness)
• Walk-through example with  a glimpse behind the curtains

• Jimena Linares (GFBio e.V.)
• Ivaylo Kostadinov (GFBio e.V.)

• AI user group @AWI
• ”Deep Learning for mapping permafrost disturbances”, Ingmar Nitze
• "Quality Control of a Marine Dataset with an Autoencoder", Felix Reimers
• "Automated flagging of a suspected​ temperature gradient error using supervised CNN architecture​", Mohamed Chouai

1. Storing data at AWI
2. Existing services
3. Roadmap
4. Questions/feedback?

1. What is RIS and which scholarly output will be used for the metrics?
2. RIS prototype 
3. Roadmap
4. Questions/Feedback

1. Data Management: Overview
2. Data Management Planing
3. Data Management: Tools
4. Issues related to DNA/RNA sampling activities 
5. Questions/Feedback

1. What is RIS and which scholarly output will be used for the metrics?
2. RIS prototype 
3. Roadmap
4. Questions/Feedback

1. How it works
2. Integration into O2A
3. Roadmap
4. Questions/Feedback

N. Anselm

App and binaries: https://gitlab.awi.de/data-logistics-support/MobileActionLog-Binaries_Utilities

Report at meereisportal.de: https://ogy.de/u5wy

Contact: Maximilian Betz || Norbert Anselm 

VC: https://awi.webex.com/awi-en/j.php?MTID=mfa13be2bdd5897800c3b17229a7adae9

Due to Pentecost vacation, we have preponed this meeting to 14.04.2021.   

• “Meet & Greet” to learn about machine learning activities @AWI
• Short presentations: AI Projects and Use Cases

  • “ML infrastructure at AWI" (Long Phan)

  • "A deep-learning approach for mapping retrogressive thaw slumps across the Arctic" (Ingmar Nitze)

  • "Deep Learning for Supporting Ocean Data Quality Control" (Sebastian Mieruch)

  • "Melt ponds and subglacial lakes – how Machine Learning can help" (Niklas Neckel)

• Open Discussion

VC: https://awi.webex.com/awi-en/j.php?MTID=ma14aff9ed1bc45d3c20a144a5e87f6aa

Due to Easter vacation, we have preponed this meeting to 24.03.2021.

1. Overview
2. Creative Commons
3. Questions/Feedback

1. Introduction to the psyplot python modul
2. How to visualize unstructured model data grids
3. How to apply data analysis
4. Examples
5. Questions/Feedback?

1. What is PANGAEA?
2. What to look out for when filling out data  submission form
3. Data paper versus  paper publication - Two complementary but not necessarily depending  processes
4. Questions/Feedback?

30.09.2020

postponed → 28.10.2020

1. Where can I store my data?
2. Which platforms are available for data processing?
3. Collaborative platform solutions at AWI and external solutions
4. Outlook
5. Questions/Feedback?

Already have an AWI account, need VPN access? helpdesk (at) awi . de 

Feedback/clarification for MOSES project participants at AWI Potsdam

>> Postponed to late Fall 2020.  New date TBA in Potsdam 

1. Machine learning, deep learning and artificial intelligence basics for beginners
2. Python libraries for ML and DL
3. Infrastructure at AWI
4. Questions/Feedback?

1. Machine learning, deep learning and artificial intelligence basics for beginners
2. Python libraries for ML and DL
3. Infrastructure at AWI
4. Questions/Feedback?

>> Postponed to 27.05 due to CV crisis

1. Machine learning, deep learning and artificial intelligence basics for beginners
2. Python libraries for ML and DL
3. Infrastructure at AWI
4. Questions/Feedback?

>>Postponed to 24.04 due to CV crisis

1. What is rasdaman?
2. rasdaman@AWI
3. Demo:  petascope web interface, jupyter notebook examples
4. Integration into GIS infrastructure  at AWI
5. Questions/Feedback?

1. Why version control?
2. Git and alternatives
3. Git concepts, ecosystem
4. Git basics
5. Hands-on demo
   1. Gitlab and Jupyterhub
6. Questions/feedback?

https://gitlab.awi.de

https://github.com/o2a-data  (GitHub repository for "O2A-data")

Documentation: GitLab Documentation

Presentation         

1. Jupyter notebooks:  basic concept
2. Hands-on JupyterHub at AWI
3. Questions/Feedback?

https://jupyterhub.awi.de;

Documentation: Jupyterhub Documentation (old Version)

Presentation