Processing Open Data using Terradue Cloud Platform
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The document discusses the Terradue cloud platform's role in advancing open data for earth sciences and addressing global societal issues such as climate change and geohazards. It outlines the challenges in utilizing earth observation open data, emphasizing the need for new partnership models, improved data accessibility, and effective communication on available services. The document highlights the fragility of open data access, the necessity for an agile legal framework, and the potential for community-driven innovation in the platform economy.
Processing Open Data using Terradue Cloud Platform
- 1. Session IV: Sustainability and business strategies Processing of Open Data using Terradue Cloud Pla<orm Hervé Caumont Open Data Projects cluster mee2ng 07-‐08th September 2015, Brussels
- 2. Point of Contact : Hervé Caumont, Program Manager http://www.terradue.com • Italian SME, created in 2006 – ESA ESRIN spin-off (Rome) • UK subsidiary, created in 2011 – Space Cluster (Harwell Oxford) • 12 start-upers – 5 different EU nationalities Cloud Services for Earth Sciences
- 3. Agenda • A criBcal need to solve helping Open science to address Societal issues • Three challenges ahead with the exploita5on of Earth observa5on Open Data • Terradue Cloud Pla<orm’s Business Model: new types of partnerships based on openness • SupporBng sustainable services: what we have learnt about Open Data
- 4. A criBcal need to solve Open Science addressing environment-‐related societal issues, globally
- 5. Our customers Earth sciences Climate Change
- 8. EO data is there
- 11. …but Earth Science applicaBons • are s2ll in some early stages. • Only a few opera2onal processes transferred to the industry, mostly within niche markets, • mainly outside of the “Open Web” and its poten2al to scale them out globally. • EO datasets remain very technical products, • with no Web-‐na2ve process matured enough, hampering innovaBons that would impact societal challenges globally. 11
- 12. The Web as a Pla<orm
- 13. Data-‐intensive science is the 4th paradigm The Internet can do more “You can be reading a paper by someone and then go off and look at their original data. You can even redo their analysis. Or you can be looking at some data and then go off and find out all the literature about this data. Such a capability will increase the ‘informaBon velocity’ of the sciences and will improve the scien2fic produc2vity of researchers” – Jim Gray, The 4th paradigm, 2009, MicrosoV Research
- 14. Three challenges ahead with the exploitaBon of Earth observaBon Open Data
- 15. 3 proverbs of Pla<orm operaBons
- 16. If you can't beat 'em, join 'em APIs Build innova2on without owning all assets
- 17. No man is an island Pla<orm economy Seek partnerships that challenge your idea If you can't beat 'em, join 'em APIs Build innova2on without owning all assets
- 18. When in Rome, do as the Romans do Network effects Exploit the Web at its full scale If you can't beat 'em, join 'em APIs Build innova2on without owning all assets No man is an island Pla<orm economy Seek partnerships that challenge your idea
- 19. Maximizing e-‐collaboraBon EC FP7 MELODIES
- 22. SenBnel-‐1 Data Access EC FP7 Sen2nels Synergy Framework
- 23. Promoting Earth Observation Services EOP <-‐> SAFE Data mirroring strategies OpenSearch protocol
- 24. Open Source InSAR Processors ESA Thema2c Plaaorms
- 26. Terradue Cloud Pla<orm’s Business Model New types of partnerships based on openness
- 27. ESA BiDS’14 Conference hbp://dx.doi.org/10.5281/zenodo.12728
- 28. Terradue Cloud Pla<orm Concept of operaBon
- 29. 29 Hosted CommuniBes 5 Climate Change Carbon market Climatology Oceanography Ship logis2cs Land management Water quality Deser2fica2on Biodiversity Urban accoun2ng Volcanology Seismic analysis Disaster Risk Reduc2on EC FP7 GEOWOW (2011-‐2013) EC FP7 SenSyF (2013-‐2015) EC FP7 MELODIES (2014-‐2016) ESA Exploita2on Plaaorms (2014 onwards) 8 14 ì 35+ H2020 EcoPoten2al (2015-‐2018) 30+ Campaigns (2013 onwards)
- 30. 30 Virtual Machines for developers my RPMs !
- 31. 31 Cloud deployments ready to scale out
- 32. 32 Cloud Storage on request
- 33. 33 Citable applicaBons & datasets
- 34. Pla<orm as a Service • Producer Decks (hybrid) • Deploy Cloud Appliance clusters on public clouds • ElasBc Catalogues • S3 data nodes • Templates (hybrid) • Community Hubs on private cloud • Define OneFlow services • Hadoop Sandboxes on private cloud • Build ApplicaBons Developers Integrators Producers Data Providers
- 36. SupporBng sustainable services What we have learnt about Open Data
- 37. We are aiming at • Rapid prototyping and benchmarking of algorithms • Seamless data access whatever stage of the process • Automated data processing for non expert users 37
- 38. What is costly ? • Open Data access is s2ll fragile, it does not inherited yet the resilience of the Web. Linked Open Data is one step ahead in that direc2on. • The required knowledge stack for valuing Open Data is widely spread, and no single organiza2on can afford the cost to control it all. • The legal constraints with dissemina2ng informa2on products based on Open Data are s2ll varied, and are 2me-‐consuming to understand well.
- 39. What we’ve learnt about Open Data • Open Data benefits cannot take up without early adopter services, growing the plaaorm with us • S2ll need to beber communicate on the available Cloud services: PaaS, DaaS, SaaS are suppor2ng the Informa2on-‐as-‐a-‐Service end game • It’s 2me to spread the word on business models for plaaorm opera2ons : Open Science, e-‐Gov, commercial, …
- 40. We can go even further ;) h`p://melodiesproject.eu h`p://www.terradue.com @MelodiesProject @terradue
- 41. References • Terradue Cloud Plaaorm – Developer Cloud Sandbox documenta2on hbp://docs.terradue.com/developer-‐sandbox • EC FP7 SenSyF – Sen2nels Synergy Framework hbp://www.sensyf.eu/ • ESA Geohazards Exploita2on Plaaorm hbps://geohazards-‐tep.eo.esa.int/ • ESA Big Data From Space Conference 2014 hbp://congrexprojects.com/2014-‐events/BigDatafromSpace/ • Cantonese proverbs J hbp://www.dramafever.com/news/81-‐cantonese-‐proverbs-‐explained-‐in-‐ one-‐beau2ful-‐poster/ 41