ENES Climate Analytics Service (ECAS)

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@EOSC_eu
EOSC-hub receives funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 777536.
ENES Climate Analytics Service (ECAS)

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Motivation and driving consideration about the service
Service architecture and interfaces: overview
- How the user can access the service
 E.g.: REST, GUI, CLIs, etc.
- Service options and attributes
Acceptable Usage Policy (AUP)
Access policy and business model
Use cases
Documentation/tutorial/information
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Content

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Traditional approach to data analysis relies on data
downloads and using local analysis tools
- Data are now too huge to download
- Data sharing and re-use are strongly desirable
ECAS provides a server-side data analysis environment
- Computationally powerful: Ophidia analytics framework
- Easy to use: Jupyter notebooks and data sharing services
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Motivation

4. Data Sources
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Service architecture and interfaces
Data Sharing
Supporting services
ECAS Work Environment
IAM

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Users can register and log-in at the ECAS instances:
- CMCC: https://ophidialab.cmcc.it/
- DKRZ: https://ecaslab.dkrz.de/
Users can develop Jupyter notebooks with Python
- Bring your own data: direct upload or use B2DROP
- Share your workflows via the ECAS workflow repository
Alternative access via the Ophidia terminal is possible
- Provides execution options for shared workflows
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Service access

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DKRZ and CMCC are the current service providers for
ECAS
The two instances can be used by users after registration
- The instances differ in the choice and amount of local data
provided. Please refer to individual site documentation for
details.
A github repo has been set up to share Python
applications and analytics workflows at
https://github.com/ECAS-Lab
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Service options and attributes

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Using the DKRZ ECAS instance requires acceptance of
DKRZ Terms of Use:
- https://www.dkrz.de/up/de-my-dkrz/de-terms-of-use
Similar terms of use are going to be published for CMCC
ECAS instance.
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Acceptable Usage Policy

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ECAS can support a mixed access policy, pending more
elaborate feedback via EOSC processes
- Excellence-driven: Inclusion of ECAS resource reqeusts as
part of proposed projects or individual service contracts.
- Market-driven: ECAS resources could be ordered in
predefined blocks or via an auction model.
The details need to be defined in collaboration with the
relevant EOSC-hub actors.
A fraction of the service may in addition be provided for
training and education purposes.
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Access policies and Funding models

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Climate index calculations
- e.g., length of snow season, monthly temperature
averages, precipitation trend analysis, number of tropical
nights
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Featured use case (I):
Climate data analysis

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Integration activity ECAS/B2DROP
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Featured use case (II):
A complete workflow for computation, viz and
sharing of a climate indicator

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Ophidia documentation:
http://ophidia.cmcc.it/documentation/
Github repo: https://github.com/ECAS-Lab
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Documentation

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