Science Platforms and the IVOA
The SKA Regional Centres Network Use Case
Jesús Salgado
SKA Regional Centres Network Architect
And the SRCNet members
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SKA Regional Centres (SRC) Network in Numbers
SKA Regional Centre Capabilities Blueprint
Interoperability
Heterogeneous SKA data from different SRCs and other observatories
Visualization
Advanced visualizers for SKA data and data from other observatories
Science Enabling Applications
Analysis Tools, Notebooks,
Workflows execution
Machine Learning, etc
Distributed Data Processing
Computing capabilities provided by the SRCNet to allow data processing
Data Discovery
Discovery of SKA data from the SRCNet, local or remote, transparently to the user
Data Management
Dissemination of Data to SRCs and Distributed Data Storage
Support to Science Community
Support community on SKA data use, SRC services use, Training, Project Impact Dissemination
SRC Network global capabilities
SRCNet Principles
Use of Standards
Build SKA science archive around FAIR and IVOA standards
Data Management
Avoid unnecessary
duplication and transfers
Roughly 5-10 million dollars per year in new data, for one copy
Collaboration and Reproducibility
Science Reproducibility at the level of workflows is essential as data should not be downloaded
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By:
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The IVOA Context
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InterOperability and
Federation
Federated Authentication
and Distributed Processing
Platforms interconnected
Data Lakes
Science Enabling Applications
Astropy and Astroquery
Notebooks
Users environments
Discovery And Access Services
Cone Search
SSAP, SIAP
TAP
Democratic Science and AI
Harmonisation
Transparent Data Access
Combined Computing Resources
Science platforms
Authentication
Interactive Analysis
Big Terminal
Batch
Authorisation
Metadata
Computing
Data
Orchestrators
SW Repository
Science Platforms Interoperability
Authentication
Interactive Analysis
Big Terminal
Batch
Authorisation
Metadata
Computing
Data
Authentication
Interactive Analysis
Big Terminal
Batch
Authorisation
Metadata
Computing
Data
Federated Authentication
API
API
Federated Data Lake
Service
Service
Orchestrators
Orchestrators
SW Repository
SW Repository
Interoperable/federated SW Repositories
Some possible data mesh services
Data Type | Operation | Input | Output |
Any Type | Get Stream | ID | Input Stream |
Data Cube | Cut-out | ra, dec, size, resolution | Data Cube |
Data Cube | Get Spectra | ra, dec, size | Spectrum |
Data Cube | Get Time Series | ra, dec, size | Time Series |
Data Cube | Get Slice | wavelength | Image |
Image | Change Resolution | ra, dec, size, resolution | Image (FITS to HiPS) |
Image | Source Extraction | ID, algorithm params | Source Catalogue |
Spectrum native | Convert to VO | ID | Spectrum VO |
Source Catalogue | Similar Source | Source ID | Source Catalogue |
The problem of the formats
Spectrum
Mission 1
Looking for
Spectrum VO
(greatest common divisor)
Spectrum
Format 1
Spectrum
Format 2
Final Spectrum VO Format
(lowest common denominator)
Translation
Server
Translation
Server
Native
VO
Execution Planner
Execution
Planner
Science
Platform I
Science
Platform II
Science
Platform III
Science
Platform IV
Solving the Topology
Execution
Planner
Information
System
Summary
PROMOTE
NEW?
EXTEND
NEW API
COMPLETE
STANDARD
Thanks for your attention
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