The BigSkyEarth conference in Sorrento, Italy, addressed the question of how to train a new generation of astronomy and Earth observation scientists in the age of interdisciplinarity driven by big data. Modern data-intensive research requires natural science students trained in software engineering, algorithms, and data mining, data management and visualization. These trends challenge the current paradigm of what constitutes education in astronomy or Earth observation. Big data trends in modern astronomy and Earth observation make those fields increasingly dependent on computer science. Actually, so dependent that often they have to be considered as new interdisciplinary fields of research. This collides with the traditional educational programs where students in astronomy and Earth observation do not receive training adequate for the era of big data.

Some of the participants at the conference.

Should young natural scientists become more similar to IT/CS professionals, or vice versa? Is this derailing students from their core research? Does this require entirely new PhD programs or students can fill their gaps in skills by taking specialized online courses? Whose job is to devise these new courses and how to motivate the research community to take the effort? How much does this shortage of young natural scientists with big data skills jeopardize the upcoming big data facilities in astronomy and Earth observation?

Here we present some of the talks given at the conference. They vary from more focused at the current data challenges to talks about education, skills and algorithms. The program is available HERE, while the book of abstracts is HERE.

Book of abstracts

EARTH OBSERVATION PARADIGM SHIFT: BIG DATA ANALYTICS Authors: Mihai Datcu Presentation in PDF.

ASSIMILATION OF ATMOSPHERIC WATER VAPOR MEASUREMENTS: HOW DATA SCIENCE CAN CONTRIBUTE TO THE VISUALIZATION AND SURFING OF INFORMATION CONTENT Authors: Giovanni NICO, Pedro MATEUS, Javier LOZANO, Joao CATALAO, Marco QUARTULLI Presentation in PDF.

DEEP LEARNING – AN INTERDISCIPLINARY VIEW OF LEARNING ALGORITHMS FOR REMOTE SENSING IMAGE ANALYSIS Authors: Dimitris Marmanis Presentation in PDF.

TEACHING ADVANCED METHODOLOGY TO ASTRONOMERS Authors: Eric D. Feigelson Presentation in PDF.

THE LSSTC DATA SCIENCE FELLOWSHIP PROGRAM Authors: Zeljko Ivezic Presentation in PDF.

DATA MANAGEMENT PLANS AND STANDARDS FOR SPACE DATA: HOW TO TRAIN FUTURE SPACE DATA PROVIDERS AND USERS Authors: Christian Muller, Praveen Pandey Presentation in PDF.

HOW CAN THE EVOLUTION OF DATA MANAGEMENT SYSTEMS HELP FOR FOR BIG DATA APPLICATIONS? Authors: Abdelkader Hameurlain Presentation in PDF.

SOFTWARE ENGINEERING PRACTICES FOR SPACE EXPERIMENTS Authors: Gottfried Schwarz Presentation in PDF.

MEANS OF COLLABORATION BETWEEN HE INSTITUTIONS AND THE RAPIDLY GROWING IT INDUSTRY IN SERBIA Authors: Boris Antic Presentation in PDF.

INFORMATICS IN ARMENIAN SCHOOLS AND THE BACKGROUND FOR ASTROINFORMATICS STUDIES Authors: Aneta Baloyan Presentation in PDF.

BIG DATA ERA IN ASTRONOMICAL EDUCATIONAL ACTIVITIES IN ARMENIA Authors: Areg Mickaelian Presentation in PDF.

BIG DATA, CLOUD AND MACHINE LEARNING AND THEIR IMPACT TO EDUCATION Authors: Blagoj Delipetrev Presentation in PDF.

FROM BIOINFORMATICS TO ASTROINFORMATICS CURRICULUM : THE FRENCH EXPERIENCE Authors: Engelbert Mephu Nguifo Presentation in PDF.

FUNDAMENTALS OF MACHINE LEARNING FOR PREDICTIVE ANALYTICS Authors: Brian Mac Namee Presentation in PDF.

HOW TO GROW AN ASTROINFORMATICIAN Authors: Petr Skoda Presentation in PDF.

THE NEED FOR A NEW GENERATION OF METEOR DATA SCIENTISTS Authors: Dejan Vinkovic, Maria Gritsevich Presentation in PDF.

ANALYSES OF ELF/VLF/LF RADIO WAVE VARIATIONS DURING THE METEOR SHOWERS Authors: Aleksandra Nina, Srdjan T. Mitrovic, Jovan Bajcetic, Darko Jevremovic Poster in PDF.

VLF REMOTE SENSING OF THE LOWER IONOSPHERE AND REAL TIME SIGNAL PROCESSING Authors: Vladimir Sreckovic, Darko Jevremovic, V. Vujcic Poster in PDF.

ALERTSIM – SERBIAN CONTRIBUTION TO LSST Authors: Darko Jevremovic, V. Vujcic, J. Aleksic, V. Sreckovic Slides in PDF. (and video of an older version of this talk)

Photos