OBIDAM'14 was made possible with support from T. Le Toullec (LPO/CNRS, technical) and F. Cudennec (IRD/LPO, administrative)
The extraction of knowledge on ocean’s dynamic at small and large scales as well as the development of regional and global indicators of climate variability are hot topics, for which new technological and methodological challenges recently emerged. Database have grown bigger and bigger (from the giga to the peta-scale) with rapid updating frequencies (from the year/month to the day/hour scale), and involve complex structures and higher dimensionality (from one file/parameter to millions of files and dozens of parameters on multiple locations). To the physical oceanographic community it has become challenging to manage, explore and extract knowledge out of such databases.
“Data Mining”, “Database Knowledge Discovery” or “Artificial Intelligence” are the names given to the research discipline dedicated to face such challenges. The school aimed at fostering interactions between the “Data Mining” and “Oceanographic” research communities and for the latter to broaden its view on available analysis tools.
The target groups of the school were postdocs, PhD students and research scientists, from all over Europe and beyond, from:
the oceanographic community who wished to broaden their analysis skills of oceanic databases (such as from Argo, Cersat and SSALTO/DUACS). They should preferably be engaged in ocean physics studies, but work in a neighboring field such as atmospheric physics/meteorology and bio- or geo-sciences may also be considered.
the data mining community seeking for new case studies and applications in the domain of environmental sciences.
OBIDAM'14 consisted of a series of invited talks covering both theoretical and practical aspects of data mining tools and methods, including applications to environmental science. It also provided the opportunity to participants to present and discuss their research work during a dedicated poster session.
Final presentations (english) and report (french) are available online, from the left main menu or the right panel shortcuts.