Dean, the School of Informatics
and Data Science
All you know Nightingale, who is called “Angel of White Coat” as she served in the Crimean war and dedicated to the injured soldiers regardless of their ally and enemies, by reading her biography in your childhood. The details how she served in the war and what she did in the barrack hospital being found in her biography, Nightingale realized that the majority of the deaths at the hospital resulted from insanitation in the hospital from her experience of nursing. After she returned home, she collected a lot of data to analyze such situations. Then she analyzed the data statistically and devised a way to explain the result clearly. The idea of "revealing real problems based on data and improving them by the data" is now a matter of course, but she practiced it and contributed greatly to the medical hygienic reform at the time. For this reason, Nightingale is called "mother of statistics" in the UK.
How about now in modern times? We can contact a huge amount of information through the Internet. By using a computer, the information can be easily processed and accumulated as data. In addition, progress in statistics, dramatic improvements in computer performance, and advances in technologies such as artificial intelligence (AI) have made it possible to analyze big data at high speed. An artificial neural network modelling the human brain is one of the examples. If Nightingale heard this, she would feel so envious of it. She spent a great deal of time and effort to collect the data. Besides, she could use only elementary statistics for data analysis.
However, accumulating huge amounts of data will create nothing because the information itself has no value. What is important is to analyze the data and how you can lead it to the knowledge, and the greatness of Nightingale is exactly in this respect. In many fields of modern society, there is a demand for human resources called "data scientists" who can gather and analyze information, and make rational judgments based on objective data.
Informatics and data science deal with this series of process; unfortunately, however, the fields which have succeeded at this time are limited, and only few topics like “Alpha Go” or automatic translation are mentioned in the newspaper. Other fields such as computer performance and maintenance, data accumulation method, theory of learning and knowledge acquisition in the field of AI are still less than satisfactory. However, informatics and data science have enormous potential and diverse application areas. Application of AI to the aging society, improvement of investment and portfolio management, automatic operation, etc., the list goes on and on. The school of Informatics and Data Science, which is newly founded at Hiroshima University, aims to contribute to our society by research and education on this attractive field through informational aspects. I hope that a lot of motivated young people get together and make this school vibrant.
Dean, the School of Informatics and Data Science
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