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Big Data from Space refers to Earth and space observation data collected by space-borne and ground-based sensors. Whether for Earth or space observation, they qualify being called ’big data’ given the sheer volume of sensed data (archived data reaching the Exabyte scale), their high velocity (new data is acquired almost on a continuous basis and with an increasing rate), their variety (data is delivered by sensors acting over various frequencies of the electromagnetic spectrum in passive and active modes), as well as their veracity (sensed data is associated with qualified uncertainty and accuracy measurements). Last but not least, the value of big data from space depends on our capacity to extract information and meaning from them. Big Data from Space is an emerging domain given the recent sharp increase in all three main dimensions of big data: volume, velocity, and variety. Fortunately, this increase is paralleled by tremendous amount of new developments related to big data in other fields and enabled by technological breakthroughs and new challenges in hardware and software developments, multi-temporal data analysis, data management and information extraction technologies. In addition, the recent multiplication of open access initiatives to big data from space is giving momentum to the field by widening substantially the spectrum of users as well as awareness among the public while offering new opportunities for scientists and value-added companies. The ambitious and unique European Union Copernicus programme whose Sentinel missions operated by the European Space Agency will deliver free and open access to global data in the microwave and optical/infrared ranges. The first one, Sentinel-1A, has been launched on the 3rd of April 2014 and is already delivering high resolution SAR global data every 12 days at a daily rate of 2.5 TB. The Conference has permitted to highlight new and emerging areas, as well as areas requiring special attention such as collaborative environments, the federation of processing capabilities, harmonization and standardization of access, and processing mechanisms allowing for the seamless deployment of approaches exploiting the full spectrum of Big Data from Space, so as to foster the generation of new and reliable meaningful information. Concerning future opportunities for business development, some key-issues have been identified, namely: quality of data (data veracity) leading to quality information for end-users; the future of space open data (data value); the identification of value chain segments; Data Public Private Partnership (cPPP) between EC and Big Data Value Association. Priorities for Research and Technology Development have been also derived, aligning with EU’s views on a data-driven economy. A preliminary list of recommendation for ESA to drive future activities in the field has been finally drawn. ESA, JRC and SatCen confirmed their availability to organise the next BiDS Conference in Spring 2
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Summary and Recommenda.ons
Main Objec+ves • Widen competences and exper.se of universi+es, research
ins+tutes, labs, SMEs, and industrial actors • Foster networking of experts and users towards be>er access and
sharing of data, tools, and resources • Leverage innova+on, spin in/off of technologies, and business
development arising from research and industry progress • Contribute towards the iden+fica+on of the priori.es for a ’Big
Data from Space’ research, development and innova.on agenda
Competences and Exper.se
• Architectures and plaKorms • Data storage management • Harmonisa+on and standards • Open and linked data • Data assimila+on • Data visualisa+on • Data processing (HW & SW) • Mul+-‐mission and mul+-‐source data
processing • Data mining
Achieving the main objec+ves
• Content based image retrieval • Mul+-‐temporal analysis • Collabora+ve environments and
federa+on of processing capabili+es • End-‐to-‐end system design • Ci+zen cyberscience &
crowdsourcing
Networking
• More than 400 par+cipants and authors, from 28 different countries • Interna+onal Organiza+ons (ESA, JRC, EU SatCen) • Na+onal Organiza+ons (CNES, DLR, ASI, NASA, NOAA, …) • Research ins+tutes, universi+es and industry • Domains covered: Earth Science, Climate Science, Astronomy, Resource
Management • Technologies covered (see previous slide) • High interac+on during industry demonstra+on sessions
Achieving the main objec+ves
Business development
Main issues: • Quality of data (Veracity), leading to quality informa+on for end user • The future of space open data • Iden+fica+on of value chain segments • Commodi+sa+on of big data infrastructures • Legisla+on framework (interoperability, data protec+on, IPR) • Big Data Public Private Partnership (cPPP) between EC and Big Data Value
Associa+on
Achieving the main objec+ves
Research, Technology Development and Innova.on Priori.es
Alignment with EU’s views on a data-‐driven economy:
• Availability of good quality, reliable data (Veracity) • Availability of interoperable datasets and enabling infrastructure (Volume &
Variety & Velocity) • Usability of data for decision-‐making processes • Improved framework condi+ons that facilitate value genera+on from datasets,
coopera+on among “players” and sharing of solu+ons • Exis+ng (EO, Science, SSA, Space engineering, …) and future applica+ons areas
where improved big data handling can make a difference
Achieving the main objec+ves
Big Data
Volume • Mul+ mission • Historical • Processed • …
Velocity • Sensor • Processing (HW/SW)
• User access (Cloud)
Variety • Sensor / systems • Processing • Applica+ons • …
Veracity • Cri+cal applica+ons • Societal needs • Business needs • Policy needs
R&D&I priori.es
1. Establish a research, technology development and Innova+on agenda in the field of Big Data from Space with several well coordinated (and unified) concept and ac+vity streams, in close and permanent dialogue with the key industry /SMEs actors
2. Foster research ac+vi+es and innova+ve solu+ons in the “Data Science” domain, in view of future downstream services
3. Coordinate the European efforts (programma+c and technical) for developing and promo+ng new models and plaKorms for Big Data from Space exploita+on (from data-‐to-‐user to user-‐to-‐data)
4. Contribute to the explora+on and implementa+on of new “partnership models” for the actual exploita+on of future Big Data flows
5. Include in technology programmes ac+vi+es suppor+ng the development in cross-‐sectorial Big Data fields
Drak Recommenda+ons (to ESA)
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