JpGU-AGU Joint Meeting 2017

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[EE] Poster

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI27] [EE] Challenges of Open Science: Research Data Sharing, Infrastructure, and Scientific Communications

Tue. May 23, 2017 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall HALL7)

convener:Yasuhiro Murayama(Big Data Integration Research Center, National Institute of Information and Communications Technology), Sean Toczko(Japan Agency for Marine-Earth Science and Technology), Baptiste Cecconi(LESIA, Observatoire de Paris, CNRS, PSL Research University), Brooks Hanson(American Geophysical Union), Kerstin Lehnert(Columbia University), Takashi Oguchi(Center for Spatial Information Science, The University of Tokyo), Yasuhisa Kondo(Research Institute for Humanity and Nature)

[MGI27-P01] Arctic Data archive System(ADS)

*Hironori Yabuki1, Takeshi Sugimura1, Takeshi Terui1 (1.National Institute of Polar Research)

Keywords:Arctic, Global Warming, ArCS

A new project of the Arctic research (ArCS :Arctic Challenge for Sustainability) has been started in 2015. ArCS is a national flagship project funded by the Ministry of Education, Culture, Sports, Science and Technology. The National Institute of Polar Research (NIPR), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and Hokkaido University are playing the key roles in this project, and will continue to carry it out for approximately four-and-a-half years from September 2015 to March 2020. Arctic Data archive System (ADS) is responsible for the data management of this project.
Arctic Data archive System (ADS), to promote the mutual use of the data across a multi-disciplinary to collect and share data sets, such as observational data, satellite data, and numerical experiment data. Through these data sets, clarify of actual conditions and processes of climate change on the Arctic region, and further contribute to assessment of the impact of global warming in the Arctic environmental change, to improve the future prediction accuracy.