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Advanced tools for guiding data‐led research processes of <scp>Upper‐Atmospheric</scp> phenomena
- Source :
- Geoscience Data Journal. 10:130-141
- Publication Year :
- 2022
- Publisher :
- Wiley, 2022.
-
Abstract
- This paper presents tools that help researchers implement the processes of data-led studies of upper-atmospheric phenomena. These tools were developed as a part of the activities of the Inter-university Upper atmosphere Global Observation NETwork (IUGONET) of Japan, which is a project to develop infrastructure for upper-atmospheric research data. This paper focuses on the data service named IUGONET Type-A, which was launched in October 2016 and has since evolved. In addition to being a conventional metadata catalogue, it has many other useful functions: an easy cross-searching system, a quick-look data-plotting procedure, an interactive data visualization system named UDAS web, and strong linkage with analysis software. Users can pick up relevant data from a huge number of data sets using either lists categorized by instruments/projects, observed regions and special campaigns or a world map of observatories. Users can quickly find the time, location and nature of phenomena that occurred by comparing the quick-look plots of various data displayed by the browser. UDAS web allows researchers to interactively create stacked plots of various data types that can facilitate the understanding of the relationships among phenomena observed in different regions. Furthermore, it presents a command list for software dedicated to data analysis that can smoothly lead users to perform detailed analyses. IUGONET Type-A provides a one-stop data service that can assist users in searching, examining and comprehending data for advanced analysis. It is also capable of handling old data, including analogue data and written paper documents. Thus, it will provide useful support for innovative interdisciplinary scientific research on solar–terrestrial phenomena.<br />超高層大気分野のデータ駆動型科学を支えるウェブサービス「IUGONET(ユーゴネット)Type-A」 --登録データセット数1200超 すでに180以上の研究成果に貢献--. 京都大学プレスリリース. 2022-07-08.
Details
- ISSN :
- 20496060
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- Geoscience Data Journal
- Accession number :
- edsair.doi.dedup.....8d35d2092c2a291fe17ab010ae4b576f
- Full Text :
- https://doi.org/10.1002/gdj3.170