LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Beech, Guy; European Commission, Joint Research Centre (2016)
Publisher: Publications Office of the European Union, Joint Research Centre
Languages: English
Types: Book
Subjects: QB, Astrophysics - Earth and Planetary Astrophysics, Photogrammetrie und Bildanalyse, Earth Observation, Remote Sensing, Future Internet, Cloud Computing, Big Data, ENTICE., Atmosphärenprozessoren, Deutsches Fernerkundungsdatenzentrum, QA75, QA76, T1, Informationstechnik

Classified by OpenAIRE into

ACM Ref: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Identifiers:doi:10.2788/854791
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 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. The goal of the Big Data from Space conference is to bring together researchers, engineers, developers, and users in the area of Big Data from Space. It is co-organised by ESA, the Joint Research Centre~(JRC) of the European Commission, and the European Union Satellite Centre (SatCen) and was held at the auditorio de Tenerife (Santa Cruz de Tenerife, Spain) from the 15th to the 17th of March 2016. These proceedings consist of a collection of 108 short papers corresponding to the oral and poster presentations presented at the conference. They are organised in sections matching the order of the conference sessions followed by the contributions that were presented during the poster session, also organised by topics. They provide a snapshot of the current research activities, developments, and initiatives in Big Data from Space.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] VAO. (2015, May 1). History of the Virtual Astronomical Observatory. Retrieved from VAO: http://virtualobservatory.org/whatis/history.aspx
    • [2] NASA. (2014, October 21). XDF: The Extensible Data Format Based on XML Concepts. Retrieved from NASA: http://nssdc.gsfc.nasa.gov/nssdc_news/june01/xdf.html
    • [3] Beech, G. (2015, October). An Investigation of the Benefit of XML Technologies in Astronomical Data Interpretation. Huddersfield University, West Yorkshire, UK.
    • [4] Lopez, M. H. (2014, November 14). The World's Technological Capacity to Store, Communicate, and Compute Information. Retrieved from Science Magazine: http://www.sciencemag.org/content/332/6025/60
    • [5] Wall, M. (2014, November 17). Astronomy Overload. Retrieved from Space.com: http://www.space.com/9308-astronomy-overloadscientists-shifting-stargazing-data-mining.html
    • [6] Mesiti, M. (2011). XML-Based Approaches for the Integration of Heterogeneous Bio-Molecular Data. In H. H. Trimm, Recent Advances in Biochemistry (pp. 206 - ). CRC Press.
  • No related research data.
  • Discovered through pilot similarity algorithms. Send us your feedback.

Share - Bookmark

Funded by projects

  • EC | ENTICE

Cite this article