9:30 AM - 9:45 AM
[MGI27-07] Analysis of the utilization status of observation data of earthquakes, tsunamis, and volcanoes in Japan based on data DOI citation information
Keywords:Data DOI, Citation information, Observation data of earthquakes, tsunamis, and volcanoes
Assigning DOIs to research data serves as the foundation of open science. Assigning a data DOI ensures sustained access to research data and is expected to further promote the use of data. Citing the data DOI in publications contributes to the evaluation of research data. Moreover, examining the citation status of data DOIs makes it possible to understand how the data is utilized. In this study, we analyzed the utilization status of observation data of earthquakes, tsunamis, and volcanoes in Japan based on data DOI citation information. The target of this study is the nationwide observation network for earthquakes, tsunamis, and volcanoes over land and sea (MOWLAS), which has been maintained and operated by National Research Institute for Earth Science and Disaster Resilience. MOWLAS comprises seven observation networks with different purposes and features (Aoi et al., 2020). This study focused on the following six data DOIs assigned to these observation networks:
High Sensitivity Seismograph Network Japan (Hi-net): 10.17598/NIED.0003
Strong-motion seismograph networks (K-NET, KiK-net): 10.17598/NIED.0004
Full Range Seismograph Network of Japan (F-net): 10.17598/NIED.0005
The Fundamental Volcano Observation Network (V-net): 10.17598/NIED.0006
Seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net): 10.17598/NIED.0007
Dense Oceanfloor Network system for Earthquakes and Tsunamis (DONET): 10.17598/NIED.0008[KS1]
We collected information on the publications citing them from the Web of Science (WoS) database and examined the citation status from 2019 to 2022. If there were any incorrect citations, the corresponding literature was excluded.
The results show that more than 160 publications citing the MOWLAS's data DOIs have been issued during the survey period, indicating that the MOWLAS's observations have been used in numerous research studies. The total number of publications has generally been increasing over the survey period. They are most frequently cited in the order of K-NET/KiK-net, Hi-net, and F-net. Furthermore, the number of citations of the publications exceeded 600, increasing annually alongside the number of publications. A comparison of the number of publications by journal was also conducted. It was found that papers using MOWLAS's research data have been published in various journals including ones with high impact factors, and the publication proportion among the data DOIs varies by journal. This is because the main research themes differ by journal, resulting in the use of different research data. Regarding the country of the first author's affiliation, over 70% of the papers are from Japan. While only about 10% of publications from networks other than K-NET and KiK-net were from outside Japan, over 40% of publications citing K-NET and KiK-net’s data DOIs originated abroad. This indicates that K-NET, KiK-net's observation data is widely used by research institutions abroad. We also analyzed the publication titles by observation network using quantitative text analysis, clarifying the relationship between the MOWLAS data and specific research trends.
This study examined the utilization status of the MOWLAS data by analyzing the data DOI citation information of WoS. It is important to analyze data DOI citation information further and conduct periodic surveys continuously. Analyzing data over a long period can capture changes in research trends using the observation data. We also consider that it is important to develop a citation indicator for data DOI citations, similar to the impact factor for paper citations. Such an indicator would allow for comparing citation status among research data, contributing to an objective understanding of research data's citation status.
High Sensitivity Seismograph Network Japan (Hi-net): 10.17598/NIED.0003
Strong-motion seismograph networks (K-NET, KiK-net): 10.17598/NIED.0004
Full Range Seismograph Network of Japan (F-net): 10.17598/NIED.0005
The Fundamental Volcano Observation Network (V-net): 10.17598/NIED.0006
Seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net): 10.17598/NIED.0007
Dense Oceanfloor Network system for Earthquakes and Tsunamis (DONET): 10.17598/NIED.0008[KS1]
We collected information on the publications citing them from the Web of Science (WoS) database and examined the citation status from 2019 to 2022. If there were any incorrect citations, the corresponding literature was excluded.
The results show that more than 160 publications citing the MOWLAS's data DOIs have been issued during the survey period, indicating that the MOWLAS's observations have been used in numerous research studies. The total number of publications has generally been increasing over the survey period. They are most frequently cited in the order of K-NET/KiK-net, Hi-net, and F-net. Furthermore, the number of citations of the publications exceeded 600, increasing annually alongside the number of publications. A comparison of the number of publications by journal was also conducted. It was found that papers using MOWLAS's research data have been published in various journals including ones with high impact factors, and the publication proportion among the data DOIs varies by journal. This is because the main research themes differ by journal, resulting in the use of different research data. Regarding the country of the first author's affiliation, over 70% of the papers are from Japan. While only about 10% of publications from networks other than K-NET and KiK-net were from outside Japan, over 40% of publications citing K-NET and KiK-net’s data DOIs originated abroad. This indicates that K-NET, KiK-net's observation data is widely used by research institutions abroad. We also analyzed the publication titles by observation network using quantitative text analysis, clarifying the relationship between the MOWLAS data and specific research trends.
This study examined the utilization status of the MOWLAS data by analyzing the data DOI citation information of WoS. It is important to analyze data DOI citation information further and conduct periodic surveys continuously. Analyzing data over a long period can capture changes in research trends using the observation data. We also consider that it is important to develop a citation indicator for data DOI citations, similar to the impact factor for paper citations. Such an indicator would allow for comparing citation status among research data, contributing to an objective understanding of research data's citation status.