This presentation was given as part of the EOSC Stakeholders Forum Scientific Community Workshop which gives the opportunity to prospective consumers and providers - from both the public and commercial sectors - to discuss needs and opportunities that should drive the definition of the EOSC service portfolio roadmap. This workshop aims to answer the following:
- What prospective needs and priorities do scientific communities have as consumers of the EOSC?
- How should EOSC facilitate the sharing of data, scientific outputs and services across national and organisational borders?
The workshop starts with a presentation of today’s state of play in federating resources and services to enable multi-disciplinary science and transnational access; it featured invited talks from representatives of digital infrastructures, research projects and communities and the long-tail of science. The workshop also involved representatives from both public and commercial organisations in their role as a service provider and service consumer. The workshop participants also took the opportunity to define a list of recommendations giving direction to the development and provisioning of the EOSC portfolio.
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Earth Science Needs and Opportunities to Define the EOSC Service Roadmap
1. Earth Science needs and
opportunities to define the
EOSC service roadmap
The 2nd EOSC Stakeholders Forum,
Vienna, November 22nd, 2018
Pedro Gonçalves
Terradue
2. Copernicus Sentinels as the next generation
Earth Observation satellites
Typical EO data volumes
500MB (S-2) < a single product < 8GB (S-1)
3. ▪ EO data is a unique source of global
measurements over decades
▪ When calibrated and combined with other sources, it
empowers validation & interpolation models
▪ Our users: Earth sciences practitioners
▪ Create, share and reuse data products
▪ Collaboration process: a feedback loop of
providers & consumers
▪ More providers of pre-processed data layers
▪ New demands for structured information
The growth model is pulled by the
communities
Earth Observation Platform
Producers
Consumers
4. Terradue
▪ Terradue is an ESA spin-off started in 2006
▪ Providing support to application builders in
Earth sciences
▪ To use satellite EO data as information source
▪ Cloud PaaS, complemented with APIs for Cloud bursting
▪ Business model: Platform-centered, a
collaborative workplace “Ellip” for value
adders to interact & co-create
5. Why value co-creation ?
▪ Since 2014 we’re evolving Terradue
Cloud Platform, user-driven, via ESA &
EU funding in a learning process
▪ Empowering user communities
accessing Earth observations and
systematic massive data processing
▪ Long-lasting partnership with EGI
▪ There is still need for significant capacity building within the
Earth sciences community in exploiting EO data
▪ At Terradue believe the value co-creation model is the way
forward to unleash innovation
7. Standardization Initiatives
▪ Earth Observation Exploitation Platform Domain Working Group
▪ A common set of functionalities ripe for standardization:
▪ Data provisioning;
▪ Information visualization and analysis;
▪ Data processing;
▪ User Authentication, Authorization,
and Accounting
▪ Next Meeting December '18 - Charlotte, North Carolina, USA
http://www.opengeospatial.org/pressroom/pressreleases/2792
8. All of it: an Open Cloud strategy
■ Open APIs
Embrace Cloud bursting APIs that can be
easily plugged into the Platform’s
codebase, so to expand the Platform offering
with Providers offering complementary
strategic advantages for different user
communities
■ Developers community
Support and nurture Cloud communities that
collaborate on evolving open source
technologies, including at the level of the
Platform engineering team, when it comes to
deliver modular extensions.
■ Self-service provisioning and
management of resources
The Platform’s end-users are able to self-
provision their required ICT resources
and to work autonomously.
■ Freedom of movement
Users are free to move data as needed.
By supporting distributed instances of
its EO Data management layer, the
Platform delivers the required level of data
locality to ensure high performance
processing with optimized costs.