FY2009-FY2014 (the first term)

  We developed the metadata database that enables cross-search of observational data distributed across some universities and institutes, and the analysis software that can handle these data in an integrated fashion. We demonstrated how these tools are useful for the upper atmospheric science, and opened various data accumulated in the IUGONET members to public. We regularly held data analysis workshops using our tools to construct the domestic and international networks for the upper atmospheric science.

FY2015-FY2020 (the second term)

  We modified the database and analysis software built in the first phase. We released a new data service, named IUGONET Type-A, for one-stop data discovery, detailed information acquisition, simple and full-scale analysis. We have also applied our standardization framework used in the above data service to projects in other fields. We held many domestic, oversea, and online analysis workshops for promoting the data usage and services handled by IUGONET and to train young researchers.


  We will continue our activities in the second phase, capacity building and data analysis workshops for the STP field. We will improve the system and update metadata in the data service "IUGONET Type-A” and release the analysis software based on MATLAB.


  We will support new data publication for upper atmospheric reanalysis data. We will also consider a workflow of data DOI assignment using IUGONET metadata. We will start to develop of analysis software based on Python.


  We will support new data publication for new instruments such as the EISCAT_3D radar. We will continue to develop an analysis software based on Python. We will construct a workflow for data DOI assignment using IUGONET metadata and contribute to the STP field data.


  We will collaborate with various projects in the STP field for accelerating the publication of a wide variety of data. We will develop high performance analysis software for data observed by new instruments. We will promote integrated analyses for a variety of data through collaborative research. We will contribute to the capacity building and the establishment of the international network through data analysis workshops in Japan and other regions.