Big Data Research

Driving reforms of smart city by big data as the core

Zhiguang SHAN, Yufei FANG

2016, 2(3): 3-8. doi:10.11959/j.issn.2096-0271.2016025

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Construction of smart city has become an important measure for national development.China’s smart city construction has already made positive progress in recent years.Big data is becoming core element of smart city construction,bringing more opportunities and challenges for the development of smart cities.The overall progress of China’s smart city construction was briefly presented.The problems of smart city in the era of big data were summarized.Some thoughts of how big data driven reforms of smart city was given as well.

Urban big data:connotation,service architecture and implementation path

Gang HUA, Dedao GU, Lianghua LIU, Yun TIAN, Haiyan XU, Dandan FANG

2016, 2(3): 9-16. doi:10.11959/j.issn.2096-0271.2016026

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In the era of big data,urban big data is the key to change the way of urban development,improve people’s living standard and offer new impetus to economic growth,so top-level design,system planning and promoting measures must be done.Firstly,the concept,connotation,boundary and classification of urban big data,and opportunities and challenges may appear in the process of developing China’s urban big data were analyzed.Then,a service architecture of urban big data which including an integrated foundation support framework,an application framework,an industrial framework,an index framework and maintenance framework was proposed.Finally,the implementation path and some suggestions to constitute the service center of urban big data were given.

Government big data opening and market utilization for smart city construction

Xuehai HONG, Lingjun FAN, Xiaonan HONG, Guojie LI

2016, 2(3): 17-26. doi:10.11959/j.issn.2096-0271.2016027

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The government big data is a large data source with high density value.Making good use of the government big data is of great benefit to promote the economic development and improve the public service.The enterprise which could propose solutions is a bridge between the government big data and the public demands.Open government big data and develop big data business market is an effective way for the government to release the value of big data.Taking the government big data of Ningbo under its smart city construction as an example,the obstacles and challenges of the government big data market utilization were analyzed,and the mode and countermeasures of the government big data market utilization were also discussed.

Challenge and countermeasure of governing government big data

Lingjun FAN, Xuehai HONG, Chao HUANG, Gang HUA, Guojie LI

2016, 2(3): 27-38. doi:10.11959/j.issn.2096-0271.2016028

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Big data is the source of the city’s wisdom,making good use of big data could solve or relieve the problems caused by the city’s development.The big data managed by the government are of high value because they are closely related to people’s life and public service.How to govern the government big data and explore its value is one of the key challenges during the construction of smart city.Taking Ningbo as a case study,the challenges of governing government big data were described,which include the needs and obstacle of sharing big data by internal government,and the problems of opening government big data and helping to bring it about market utilization,solutions and policies were also proposed.

Big data analysis and knowledge discovery for smart city development enhancement

Cong CHEN, Guohui ZHANG, Xiaolei MAXiaolei, Yinhai WANGYinhai

2016, 2(3): 39-48. doi:10.11959/j.issn.2096-0271.2016029

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Big data have been valuable asset with the widespread internet availability,and big data analyses have gain increasing popularity among international researchers.Comparing to traditional data analysis,big data analyses are able to provide more accurate results to facilitate the development smart city system.The basic knowledge,historical development and features of smart city and big data concepts were summarized,in order to provide theoretical foundations for contemporary research in smart city and big data fields.

Population inflow and outflow of Beijing and Shanghai based on big data analysis

Xiaojin ZHOU, Yang YAO

2016, 2(3): 49-59. doi:10.11959/j.issn.2096-0271.2016030

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With the help of LBS big data analysis,more about population floating and its changing is know while the outcome is more accurate and its cost less than traditional population investigation or census.Analysis shows that the population size from outside province of Beijing and Shanghai remains stable with a slight decline by the end of 2015.Compared with national population census of 2010,the inflow population structure has seen a great change,the inflow population from the neighboring provinces increased a lot.To speed up the implementation of the national big data strategy,the government should promote public data sharing,attract more scholars to engage in big data analysis and help to build the country's basic population database.

Research on public perception changes of the sudden environmental pollution event based on MicroBlog

Zhiheng ZHANG, Xingpeng CHEN, Dan HUI

2016, 2(3): 60-72. doi:10.11959/j.issn.2096-0271.2016031

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Exploring how the characteristics of public perception changes in sudden environmental pollution events is significant to make decisions in emergency.Taking the 2014 Lanzhou water pollution event as an example,by using the data from Sina MicroBlog and the content-analysis method,the characteristics of how public perception changes and its six directions were measured.Result shows that the small text set which reflects people’s follows Zapf’s law.Public perception experienced four periods:convergence,stable,divergence,and public reflection.According to the sensitivity,public perception directions can be divided into “light sensitive” and “strong sensitive”.Based on analysis of periods in public perception and the characteristics of how public perception changes and its directions,suggestions were given on dealing with sudden environmental pollution events.

Distributed processing practice of the massive GIS data based on HBase

Xuemei LI, Junfeng XING, IUDawei L, Haiyang WANG, Wei LIU

2016, 2(3): 73-82. doi:10.11959/j.issn.2096-0271.2016032

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Based on the distributed database HBase,a kind of GIS data management system was designed.The system optimized the generated and stored procedures of raster data,which could be directly written into the storage and indexing of the HBase.At the same time,in view of the storing,indexing and retrieval of the vector spatial data,a new design for rowkey was proposed that considering both the latitude and longitude,and the spatial data types and attributes.So that the data needed to be returned could be quickly located by rowkey of the HBase,when retrieving vector geographic information according to the spatial location.The above methods had been verified on the HBase cluster environment with real GIS data.The results show that the proposed system has high performance for storage and retrieval of mass data,and realizes the efficient storage and real-time high-speed retrieval of the vast geographic information data.

Research on data schema and security in data governance

Chaohui MA, Ruihua NIE, Haoxiang TAN, Jiaming LIN, Xinming WANG, Hua TANG, Jinji YANG, Gansen ZHAO

2016, 2(3): 83-95. doi:10.11959/j.issn.2096-0271.2016033

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One of the key objectives of big data governance is to maximize the value and efficiency of data usage.It is less than possible to privacy while processing data that has been subjected to data governance.With case study,the way to improve data value and data processing efficiency by re-construct data schemas was investigated.A mechanism for calculating new access control policies was also presented.The generated access control policies could provide appropriate security protection over reconstructed data.

Key technical challenges in telecom big data

Jia ZENG, Shikai LIU, Mingxuan YUAN

2016, 2(3): 96-105. doi:10.11959/j.issn.2096-0271.2016034

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Big data has been improving steadily user experience and productivity.Telecom big data comes from the telecommunication platform composed of the BSS (business supporting system) and OSS (operation supporting system),which accumulate billions of customers’ 7-dimensional (7D) data including 1D for real ID,1D for customer behavior data,1D for social network,1D for time series and 3D for spatial information.Telecom big data platform can support modeling of 7D customer data,which enables three business upgrades,including customer insight,network insight and data openness.9 technical challenges of telecom big data analytics and possible solutions were described and discussed.

Training data scientists in the era of big data

Yangyong ZHU, Yun XIONG

2016, 2(3): 106-112. doi:10.11959/j.issn.2096-0271.2016035

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In the age of big data,data scientist has become a hot occupation,supplanting traditional information scientist and big data engineer.Big data boom has been pushing data science research into fast development phase.How to train data scientists has been paid widespread attentions.Many universities launched data science degree training plans.The current situations in data scientists training were analyzed.The achievements of training data scientists in Fudan University were summarized.A systematical data scientists training plan was proposed.

Application of big data in China Telecom

2016, 2(3): 113-120. doi:10.11959/j.issn.2096-0271.2016036

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