TY - GEN
T1 - Analytical toolbox for smart city applications
T2 - 5th IEEE International Conference on Big Data, Big Data 2017
AU - Komamizu, Takahiro
AU - Nakazawa, Jin
AU - Amagasa, Toshiyuki
AU - Kitagawa, Hiroyuki
AU - Tokuda, Hideyuki
N1 - Funding Information:
The authors are grateful to Fujisawa city, Japan for their cooperation for data provision and discussion on this research. This research was partly supported by the program Research and Development on Real World Big Data Integration and Analysis of RIKEN, Japan.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Analyzing and feeding back the results on real-world services are important missions in the Big Data era to realize smart city. However, analyzing real-world data is still challenging because of dirtiness of data and large variety of analytic requirements. To cope with the challenges, this paper proposes and develops an analytical toolbox for smart city applications. The analytical toolbox consists of three phases: preparation, analysis, and visualization. The preparation phase deals with the dirtiness of the data by including fundamental data cleansing techniques and data integration techniques. The analysis phase is responsible for ETL (extract, transform and load) process and analytical query processing from the next phase. The visualization phase deals with analytical requirements from users and visualization of analytical results. This paper showcases a real-world use case of the proposed analytical toolbox. The use case is now open in public with help of Fujisawa city, Japan, and this fact indicates that the proposed analytical toolbox is feasible for real-world data analysis and feeding back to citizens.
AB - Analyzing and feeding back the results on real-world services are important missions in the Big Data era to realize smart city. However, analyzing real-world data is still challenging because of dirtiness of data and large variety of analytic requirements. To cope with the challenges, this paper proposes and develops an analytical toolbox for smart city applications. The analytical toolbox consists of three phases: preparation, analysis, and visualization. The preparation phase deals with the dirtiness of the data by including fundamental data cleansing techniques and data integration techniques. The analysis phase is responsible for ETL (extract, transform and load) process and analytical query processing from the next phase. The visualization phase deals with analytical requirements from users and visualization of analytical results. This paper showcases a real-world use case of the proposed analytical toolbox. The use case is now open in public with help of Fujisawa city, Japan, and this fact indicates that the proposed analytical toolbox is feasible for real-world data analysis and feeding back to citizens.
KW - Analytical toolbox
KW - Data analytics
KW - Smart city application
UR - http://www.scopus.com/inward/record.url?scp=85047728043&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85047728043&partnerID=8YFLogxK
U2 - 10.1109/BigData.2017.8258429
DO - 10.1109/BigData.2017.8258429
M3 - Conference contribution
AN - SCOPUS:85047728043
T3 - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
SP - 4105
EP - 4110
BT - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
A2 - Nie, Jian-Yun
A2 - Obradovic, Zoran
A2 - Suzumura, Toyotaro
A2 - Ghosh, Rumi
A2 - Nambiar, Raghunath
A2 - Wang, Chonggang
A2 - Zang, Hui
A2 - Baeza-Yates, Ricardo
A2 - Baeza-Yates, Ricardo
A2 - Hu, Xiaohua
A2 - Kepner, Jeremy
A2 - Cuzzocrea, Alfredo
A2 - Tang, Jian
A2 - Toyoda, Masashi
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 December 2017 through 14 December 2017
ER -
