TY - GEN
T1 - Distribution system for japanese synthetic population data with protection level
AU - Murata, Tadahiko
AU - Date, Susumu
AU - Goto, Yusuke
AU - Hanawa, Toshihiro
AU - Harada, Takuya
AU - Ichikawa, Manabu
AU - Lee, Hao
AU - Munetomo, Masaharu
AU - Sugiki, Akiyoshi
N1 - Funding Information:
The authors thank Dr. Naoki Kodama in the Department of Occlusal and Oral Functional Rehabilitation at Okayama University of Medical and Dental Hospital for performing the prosthesis treatment for the maxillary anterior edentulous region. The authors also thank Dr. Takamaro Sato of the Department of Periodontal Science at Okayama University of Medical and Dental Hospital for performing the periodontal maintenance and the treatment of periodontal diseases
Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/2
Y1 - 2020/12/2
N2 - In this paper, we introduce a distribution system of synthesized data of Japanese population using Interdisciplinary Large-scale Information Infra-structures in Japan. Synthetic population is synthesized based on the statistics of the census that are conducted by the government and publicly released. Therefore, the synthesized data have no privacy data. However, it is easy to estimate the compositions of households, working status in a certain area from the synthetic population. Therefore, we currently distribute the synthesized data only for public or academic purposes. For academic purposes, it is important to encourage scholars or researchers to use a large-scale data of households, we define protection levels for the attributes in the synthetic populations. According to the protection levels, we distribute the data with proper attributes to those who try to use them. We encourage researchers to use the synthetic populations to be familiar to large-scale data processing.
AB - In this paper, we introduce a distribution system of synthesized data of Japanese population using Interdisciplinary Large-scale Information Infra-structures in Japan. Synthetic population is synthesized based on the statistics of the census that are conducted by the government and publicly released. Therefore, the synthesized data have no privacy data. However, it is easy to estimate the compositions of households, working status in a certain area from the synthetic population. Therefore, we currently distribute the synthesized data only for public or academic purposes. For academic purposes, it is important to encourage scholars or researchers to use a large-scale data of households, we define protection levels for the attributes in the synthetic populations. According to the protection levels, we distribute the data with proper attributes to those who try to use them. We encourage researchers to use the synthetic populations to be familiar to large-scale data processing.
KW - Japanese synthetic populations
KW - Large-scale data processing
KW - Protection level
KW - Real-scale social simulations
UR - http://www.scopus.com/inward/record.url?scp=85113764202&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113764202&partnerID=8YFLogxK
U2 - 10.1109/ICMLC51923.2020.9469550
DO - 10.1109/ICMLC51923.2020.9469550
M3 - Conference contribution
AN - SCOPUS:85113764202
T3 - Proceedings - International Conference on Machine Learning and Cybernetics
SP - 187
EP - 193
BT - Proceedings of 2020 International Conference on Machine Learning and Cybernetics, ICMLC 2020
PB - IEEE Computer Society
T2 - 19th International Conference on Machine Learning and Cybernetics, ICMLC 2020
Y2 - 4 December 2020
ER -