The Great East Japan Earthquake of 2011 had profound impacts in various ways because it was a complex disaster. In addition to the earthquake itself, the tsunami and nuclear accident were even more severe for human lives, health, economy, and the environment. Researchers around the world responded to the disaster. The study topics spanned from natural sciences to social sciences. In this study, we analyzed over 20,000 academic records concerning the Great East Japan Earthquake from a data science perspective. As a result of text mining, the characteristics of many research fields were elucidated. By collecting the studies in terms of country and research subject, we found characteristics of countries that conducted studies on the disaster. We found that countries in the same Asian region as Japan and countries prone to frequent earthquakes and tsunamis have a high research interest. With the possibility of such a catastrophe in the future in mind, we should prepare ourselves by learning from previous studies to take better countermeasures next time.
The purpose of this chapter is to propose measures required for promoting coexistence with multi-culture residents (MCR). In this chapter, the plans and ordinances established by the local governments in Japan were focused. As a result, majority of the local governments targeted for the survey had declared the need for multicultural co-existence and multilingual communication of information in their plans. Further, on the web operated by the local governments, machine translation was used. However, the study revealed that there were no local governments that communicated ordinances on the web in multiple languages. Not being informed about ordinances is detrimental to the daily life of foreigners residing in the local community and further can become the cause of increase in troubles with the Japanese in the local community. Therefore, this chapter proposes that the concerned local governments translate the ordinances ranked higher in the system of all ordinances on a priority basis and collaborate with the MCR to generate more precise expressions.
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