Big Data Research

Open Data:Concepts,Status and Opportunities

Feng Gao

2015, 1(2): 9-18. doi:10.11959/j.issn.2096-0271.2015014

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Making data flow like liquid is at the heart of this so-called “Data Revolution” age.Open data movement,influenced by open source movement,advocates that government data but also private-sector data,third-sector data,and even particular type of personal data should be opened up for public interest.Therefore,what is open data,how the movement advanced thus far,the global status of the movement,potential for business,and status and challenges of the movement in China were reviewed and summarized.

Status and Safeguard Mechanisms of Chinese Government Data Opening

Daming Zhou

2015, 1(2): 19-30. doi:10.11959/j.issn.2096-0271.2015015

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Based on the development of foreign government data opening,the important characteristics of foreign government data opening were summarized,including the perfect laws and regulations system,professional data open web site and application needs guidance.The necessity of opening China government data was analyzed from requirement of data opening in the big data era,improving the governance capability and promoting the innovation development.The problems of government data opening in our country in the aspects of law,regulation,system,consciousness and management were summarized.The countermeasures and suggestions were proposed from the aspects of building code and standard system,data opening and sharing mode,government data opening management,data security and data application.

Open Data and Government Governance Innovation

Yonghua Pan

2015, 1(2): 31-37. doi:10.11959/j.issn.2096-0271.2015016

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Cloud computing makes data sharing,data flow,open data become possible,data becomes the key engine for stimulating productivity.Data is changing from the output of IT system or auxiliary role to assets and production factors.Data is driving big data market from concept phase to practice phase.Therefore,the domestic and foreign data open development process was introduced.The challenges of governance and data open faced significant value were discussed.The practice and direction of the domestic and foreign government governance innovation using open data were analyzed.The challenges and development proposals of China's government open data were proposed.

Reflections on Big Data Exchange of China

Qi Yang, Nanning Gong

2015, 1(2): 38-48. doi:10.11959/j.issn.2096-0271.2015017

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Data circulation is the decisive factor realizing big data value.The benefits of big data in social management and economic development are highly restricted because of immature of data exchange market of China.Based on the contrast analysis of the data circulation market,awareness was proposed that the data exchange was mainly hindered by the integrity of the value chain as well as the fear of business secret and personal privacy leakage.Finally,solutions were advised from the following aspects:the commercialization of data,the establishment of social cognition,the protection of the rights and interests of market entities.

Discussion on the Legal Core Question of the Data Ownership in Big Data Trade

Rong Wang

2015, 1(2): 49-55. doi:10.11959/j.issn.2096-0271.2015018

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The clear property right is the fundamental precondition of trade.However,the question of the data property right is still far not reached a consensus in the current.Especially in the circumstance of removal of personal identity attribute data,who has the property right of the anonymous data,the data subject or the enterprise that record the data? The author puts forward an exploratory opinion that for the original personal data,the data subject owns his data.For the fully anonymous data sets based on the raw data,the enterprise that record the data should be entitled a restricted ownership on it.

Networking Challenges in the Big Data Era

Weiqiang Sun, Weisheng Hu

2015, 1(2): 56-65. doi:10.11959/j.issn.2096-0271.2015019

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Explosive growth of traffic demand both inside and between data centers has resulted in a new wave of cutting edge research in the networking community.Inter-and Intra-data center research problems were identified and various solutions aiming to reduce networking cost or increase energy efficiency have been investigated.The growth in traffic demand in the big data era was accompanied by distinct characteristics in flow size distribution and delay tolerance.Data volume was dominated by large flows that are very few in number,and such flows are typically delay tolerant.How these characteristics may be used to tackle the challenge was discussed,followed by our recent work in big data transmission.The BLOC (blocking loss curve) framework aims to provide a framework with which hybrid switching systems combining packet and circuit switching can be studied.The time-shifted multi-layer graph is a generic tool that can be used to analyze the performance of circuit switched networks with bulk storage.

Abnormal Group Mining:Framework and Applications

Yun Xiong, Yangyong Zhu

2015, 1(2): 66-77. doi:10.11959/j.issn.2096-0271.2015020

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Abnormal groups can be found in a wide range of areas.Together with clustering and outlier detection,their goals are all to partition a data set according to data similarity.However,abnormal group mining (AGM) is different in problem definition,algorithm design and applications.To the best of our knowledge,the abnormal group mining problem was investigated systematically.The differences among AGM,clustering and outlier detection were analyzed.The formalized definitions on AGM and a framework algorithm were presented,and several interesting applications were particularized.

Big Data in Healthcare:Applications and System Analytics

Cheng Dong, Li Lin, Hai Jin, Xiaofei Liao

2015, 1(2): 78-89. doi:10.11959/j.issn.2096-0271.2015021

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Starting with big data and big data in healthcare,firstly,challenges and improvements of big data in healthcare were elaborated.Then the background of big data and healthcare industry was presented.Finally,big data applications in healthcare were illustrated,and analysis on the systems of big data in healthcare and their key technologies were made.

Ten Fronties for Big Data Technologies (Part A)

2015, 1(2): 100-111. doi:10.11959/j.issn.2096-0271.2015023

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Uncovering the Risk in Bank Loans by Big Data

2015, 1(2): 112-115. doi:10.11959/j.issn.2096-0271.2015024

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