Big Data Research

Scientific data cloud construction and service of Chinese Academy of Sciences

Jianhui LI, Yuanchun ZHOU, Lianglin HU, Feng LIU, Yanhua ZHU, Zhihong SHEN, Zhangsheng WU, Yang ZHANG

2016, 2(6): 3-13. doi:10.11959/j.issn.2096-0271.2016061

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Scientific Data Resource Integration and Sharing Project is one of the 5 major informatization-specific projects of CAS for the 12th Five-Year Plan period.The overall construction of the project ideas,construction,technical innovation and service innovation,etc.,was summarized.By the end of the project,a distributed mass storage environment with storage capacity of 52 PB was built.At the same time,it provided users with a strong connection between scientific data and literature and a rich visual display platform.The project has initially achieved a multi-level,cross information service system that included the infrastructure cloud service,research data cloud service and data application cloud service.It has gradually become a national science and technology data center for open sharing and service innovation.

Large scale distributed scientific data management and service technology framework and system

Feng LIU, Xin CHEN, Jianhui LI, Ang LIU, Fang HAN

2016, 2(6): 14-24. doi:10.11959/j.issn.2096-0271.2016062

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With the development of the information process,problems in the management and application of large-scale distributed With three decades of experience in related fields,after studying key issues and core requirements,the systematic toplevel design was conducted.The technical architecture for large-scale distributed scientific data in management and services was proposed,and the service system was organized and planned from three levels:autonomy management,integration management and integration services,also a complete service platform and software system were constructed to provide integration solutions for scientific data management and services from management to application.

Research data openness:development,models and new exploration

HANG Z, LI Lili,

2016, 2(6): 25-33. doi:10.11959/j.issn.2096-0271.2016063

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The concept and clarification of research data were analyzed.Judging from the aspects of principals,policies,technologies and procedures,the current state of research data openness was described.The practices have been summarized into three main kinds with top-down model,down-top model as well as horizontal-vertical model for research data openness.Further analysis shows that,besides the government forces,we still need more incentives to increase the willingness to open research data while the research data publication provides another effective solution.Take "China Scientific Data"for example,as a scholar journal publishing scientific data TOPIC:SCIENTIFIC DATA AND APPLICATION INNOVATION,it may help to promote research data open in a way.

Constructing iFlora cloud platform for botany big data integration and public service

Yanan WANG, Huifu ZHUANG, Yuhua WANG

2016, 2(6): 34-42. doi:10.11959/j.issn.2096-0271.2016064

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A construction plan of iFlora cloud platform was proposed.The validity and necessity of this platform were explained.The data demands and the working foundations were introduced.The construction frame was designed.And its applications were prospected.The platform will concentrate on the scientific data of Chinese plant species,including data of species name,reference,photo,DNA sequence,specimen,biogeography data,germplasm,cultivation and usage value.Technically,it will be based on the resource layer,the communication layer and the service layer to collect,integrate and manage the botany data.Functionally,it will be available for science research,governmental decision-making and public education in different ways,such as user interface,data interface and the data analysis service.

Constructing the international database management system for omics big data

Wenming ZHAO, Sisi ZHANG, Bixia TANG, Tingting CHEN, Lili HAO, Jian SANG, Rujiao LI, Jingfa XIAO, Zhang ZHANG

2016, 2(6): 43-52. doi:10.11959/j.issn.2096-0271.2016065

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Omics data are the important elements of the biosciences,in recent years,with the rapid progress of the next generation sequencing (NGS) technology,the omics data show the explosive increasement.Drawing on the successful experiences from the international data centers,and considering the domestic requirements,lots of databases including genome sequencing archive,genome warehouse,gene expression nebulas,genome variation map,DNA methylation databank were constructed.These databases constitute the domestic omics data resources and provide the free service for all the scientists for the data storing,sharing and management.

Exploration of crowdsourcing in information extraction from remote sensing images

Jianghua ZHAO, Xuezhi WANG, Qinghui LIN, Jianhui LI, Yuanchun ZHOU

2016, 2(6): 53-64. doi:10.11959/j.issn.2096-0271.2016066

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Based on geospatial data cloud(GSCloud),the application of crowdsourcing in large scale information extraction from satellite images was studied,and a systematic architecture of this paradigm was proposed.By performing an experiment of extracting lakes on Qinghai-Tibetan plateau from landsat images,various aspects of the paradigm like the incentive mechanism,task assignment method,task division and many others were explored.Results show that paying part of the reward in advance and assigning a task to a team instead of individuals do not help attracting more applicants and improving the quality of results.And the accumulation of talents is of critical importance to obtain high-quality task results.Since this paradigm integrates crowdsourcing and machine computing power,and it is generic,it can be applied in more massive remote sensing image processing work which requires much human intervention.

Big data and paradigm shift for astronomy in the 21^stcentury

Yanxia ZHANG, Chenzhou CUI, Yongheng ZHAO

2016, 2(6): 65-74. doi:10.11959/j.issn.2096-0271.2016067

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With the development of large space-based and ground-based observational technologies,the volume,output rate and complexity of astronomical data rapidly increase.The astronomy steps into a new data-intensive era.The characteristics of astronomical data were represented.The limitations of traditional astronomy were analyzed.The necessity and research direction of developing astrostatistics and astroinformatics were put forward.As a typical astronomical application,the operation and applications of LSST were introduced.The organizations related to astrostatistics and astroinformatics were summarized.The present situation and problems of public education about this respect were analyzed.All these were provided as references for the healthy development of big data in astronomy.

Conceptual research of the cloud platform scheme for SKA data centres

Lingling WANG, Baoqiang LAO, Yang LU, Xiaocong WU, Shaoguang GUO

2016, 2(6): 75-82. doi:10.11959/j.issn.2096-0271.2016068

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The cloud platform concept of the data center of the square kilometre array (SKA) was investigated,aiming at the big data storage and management requirements of the data centres of SKA.Based on some research of the industry development,the preliminary tests of the construction of data center "private cloud" were presented here,including a specific astronomical processing software deployment and operation in the cloud platform.

e-Science practice and results in space science under an era of big data

Ziming ZOU, Jizhou TONG, Senlin XIONG, Xiaoyan HU, Zhen JI

2016, 2(6): 83-96. doi:10.11959/j.issn.2096-0271.2016069

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With the development of space exploration technology and the deepening of space cognition,more and more space science exploration projects have been advanced and implemented,which promoted the era of big data in space science.The foreign e-Science construction status in space science and two supporting and service information systems of China Space Science Data Center(CSSDC) were described.More specifically,it presented the application environment of big data in the e-Science project of CSSDC:Space Science Virtual Observatory(VSSO),as well as illustrated the comprehensive application platform of space science in cloud environment:Solar-Terrestrial and Astronomy Research Network (STARNetwork).

Theory and progress of active operation and maintenance of mobile internet based on big data

Weimin YANG

2016, 2(6): 97-109. doi:10.11959/j.issn.2096-0271.2016070

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The relationship between user＇s perception and network performance index was studied.A five-element-five-phase (FEFP) method based on substitution between sample and space was proposed.Active operation and maintenance mode based on network performance management,can quickly find out the performance of the network in the imbalance between the nodes,abnormal trend of hidden problems etc with active network analysis.According to the analysis of the initiative,the engineers can target for exact optimization,reduce the costs,improve the quality of the network and customer satisfaction before the failure occurred.

Modeling contextual big data for user behavior prediction

Shu WU, Qiang LIU, Liang WANG

2016, 2(6): 110-117. doi:10.11959/j.issn.2096-0271.2016071

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In the big data era,information system has to handle a mass of data of contextual information,such as public opinion,environment information and economic status.Embedded with abundant details of user behavior,contextual information plays a significant role in effectively shaping user character and elaborately modeling user behavior.Two frameworks to model general context information through representation learning and a recurrent model for sequential context scenarios were involved.

Research and practice on online data production platform

Feng ZHANG, Zongzhe SUN, Dennis Reagan OCHORA, Jiannan LIU, Jie SONG

2016, 2(6): 118-128. doi:10.11959/j.issn.2096-0271.2016072

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In the big data era,the research institutes and enterprises manage massive scientific data of various disciplines,such as oceanography,meteorology,geology and petroleum,and service the clients with the analysis results that are treated as data products.Traditionally,these institutes do not provide the service-oriented production platform for data products.The shortages and challenges of the production process were analyzed,the new requirements of online production platform for scientific data product was proposed,the architecture of platform was designed,and key techniques including the serviceoriented interface for data analysis algorithms,mechanisms of data security and isolation,and the pricing model for data product were studied.Finally,the application of online production platform as a case study was explained.

Legislation and enforcement of cross-border data flows rules in Russia

Bo HE

2016, 2(6): 129-134. doi:10.11959/j.issn.2096-0271.2016073

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With the rapid development of global digital economy,the cross-border data flows are becoming an important issue of concern.For the sake of data security,Russia has imposed a strict limitation on cross-border data flows.The legislation system of Russian＇s data regulation and the establishment of cross-border data flows rules were discussed in detail and the reasons of local retention requirement in Russia were analyzed either.In the end,several suggestions were given.

Four features of industrial ecology

2016, 2(6): 2016074. doi:10.11959/j.issn.2096-0271.2016074

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