*Yoshimasa Tanaka1,7,8, Shuji Abe2, Atsuki Shinbori3, Shun Imajo4, Satoru UeNo5, Masahito Nose6
(1.National Institute of Polar Research, 2.International Research Center for Space and Planetary Environmental Science, Kyushu University, 3.Institute for Space-Earth Environment Research (ISEE), Nagoya University, 4.Data Analysis Center for Geomagnetism and Space Magnetism, Graduate School of Science, Kyoto University, 5.Astronomical Observatory, Graduate School of Science, Kyoto University, 6.School of Data Science, Nagoya City University, 7.Polar Environment Data Science Center, ROIS-DS, 8.Graduate Institute for Advanced Studies, SOKENDAI)
Keywords:upper atmosphere, metadata, database, analysis tool, interdisciplinary study
We present the activities of the Inter-university Upper atmosphere Global Observation NETwork (IUGONET) project. IUGONET is an inter-university project which aims to promote sharing and utilizing the upper atmospheric data distributed across Japanese universities and institutes. The upper atmosphere is affected by energy inputs from the space (e.g., solar radiation, solar wind, and particle precipitation from the magnetosphere) as well as inputs from the lower atmosphere (e.g., atmospheric gravity waves). In addition to such a vertical coupling, horizontal circulation over a wide area from the equator to the poles is also essential in this region. Thus, it is important to comprehensively analyze a wide variety of data obtained from global ground-based observations, satellite observations, and numerical simulations. For this reason, a transdisciplinary approach has developed in this field. In order to utilize such a variety of data, we have developed metadata databases and integrated analysis tools. The metadata database is a database in which metadata of various data are registered, allowing data retrieval, display of metadata, and visualization of data. We adopted the Space Physics Archive Search and Extract (SPASE) metadata model, which is a standardized metadata for heliophysics. The integrated analysis tool enables users to seamlessly analyze various types of data. The actual data are published mainly in the self-describing data formats Common Data Format (CDF), Network Common Data Form (NetCDF), and Flexible Image Transport System (FITS), and they are automatically downloaded to the user's PC by using the analysis tool via the Internet. We believe that our experience and know-how in database and tool development are useful for transdisciplinary study. In the presentation we will discuss the application of our methods to transdisciplinary study.