Big data has attracted much attention from academia and industry.But the discussion of big data is disparate,fragmented and distributed among different outlets.This paper conducts a systematic and extensive review on ...Big data has attracted much attention from academia and industry.But the discussion of big data is disparate,fragmented and distributed among different outlets.This paper conducts a systematic and extensive review on 186 journal publications about big data from 2011 to 2015 in the Science Citation Index(SCI)and the Social Science Citation Index(SSCI)database aiming to provide scholars and practitioners with a comprehensive overview and big picture about research on big data.The selected papers are grouped into 20 research categories.The contents of the paper(s)in each research category are summarized.Research directions for each category are outlined as well.The results in this study indicate that the selected papers were mainly published between 2013 and 2015 and focus on technological issues regarding big data.Diverse new approaches,methods,frameworks and systems are proposed for data collection,storage,transport,processing and analysis in the selected papers.Possible directions for future research on big data are discussed.展开更多
In order to conduct research and analysis on the construction of application-oriented undergraduate data science and big data technology courses,the professional development characteristics of universities and enterpr...In order to conduct research and analysis on the construction of application-oriented undergraduate data science and big data technology courses,the professional development characteristics of universities and enterprises should be taken into consideration,the development trend of the big data industry should be scrutinized,and professional application-oriented talents should be cultivated in line with job requirements.This paper expounds the demand for capacity-building professional development in application-oriented undergraduate data science and big data technology courses,conducts research and analysis on the current situation of professional development,and puts forward strategies in hope to provide reference for capacity-building professional development.展开更多
The journal Genomics, Proteomics ＆ Bioinformatics （GPB） is now inviting submissions for a special issue （to be published in the summer of 2018） on the topic of＂Big data in brain science＂.
The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenti...The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. One paper on Cloud Computing published in Vol. 18, Issue. 1, 2013, has been ranked the top of IEEE download list continuously for five months：展开更多
The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenti...The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. One paper on Cloud Computing published in Vol. 18, Issue 1, 2013, has been ranked No. 1 of IEEE download list continuously for five months： http：//ieeexplore.ieee.org/xpl/browsePopular.jsp？topArticlesDate=August＋2013.展开更多
The value of big data in science of science for knowledge discovery is that it can reveal deeper information and knowledge, promote knowledge integration in the whole process of scientific research, guide interdiscipl...The value of big data in science of science for knowledge discovery is that it can reveal deeper information and knowledge, promote knowledge integration in the whole process of scientific research, guide interdisciplinary integration, and provide new ideas and new methods for knowledge discovery research. This paper discusses the value and role of big data in science of science in knowledge discovery from five aspects, including exploring the laws of scientific research, revealing scientific structure, analyzing scientific research activities, supporting technical recognition and prediction, and serving science and technology evaluation.展开更多
Science and Technology(S&T)evaluation plays a baton role in developing science and technology innovation.However,traditional S&T evaluation indicators and methods are difficult to apply effectively in S&T ...Science and Technology(S&T)evaluation plays a baton role in developing science and technology innovation.However,traditional S&T evaluation indicators and methods are difficult to apply effectively in S&T evaluation practice.This paper analyzes the transformation of the S&T evaluation paradigm in the digital environment.Theories,methods,and tools of S&T evaluation research are continuously innovated and optimized;big data becomes the driving force of S&T evaluation development;the role played by S&T evaluation is shifting from a provider of statistical data and information to a participant in S&T decision-making activities.S&T evaluation research should focus on improving data retrieval and organization,knowledge mining and knowledge discovery,and intelligent evaluation models.Moreover,we suggest that scientists carry out S&T evaluation in agreement with the needs of S&T development:1)monitoring and sensing the development of science and technology in real-time with the help of emerging digital technologies;2)exploring solutions to major concerns such as technical project management mechanisms,utilizing advanced data science and digital technologies to identify important scientific frontiers,and leveraging big data in science of science to reveal patterns and characteristics of scientific structures and activities;3)carrying out problem-oriented evaluation research practice focused on four aspects,including intelligent project evaluation,evaluation of the critical technology competitiveness,talent assessment,and diagnostic evaluation of the research entity competitiveness.展开更多
文摘Big data has attracted much attention from academia and industry.But the discussion of big data is disparate,fragmented and distributed among different outlets.This paper conducts a systematic and extensive review on 186 journal publications about big data from 2011 to 2015 in the Science Citation Index(SCI)and the Social Science Citation Index(SSCI)database aiming to provide scholars and practitioners with a comprehensive overview and big picture about research on big data.The selected papers are grouped into 20 research categories.The contents of the paper(s)in each research category are summarized.Research directions for each category are outlined as well.The results in this study indicate that the selected papers were mainly published between 2013 and 2015 and focus on technological issues regarding big data.Diverse new approaches,methods,frameworks and systems are proposed for data collection,storage,transport,processing and analysis in the selected papers.Possible directions for future research on big data are discussed.
文摘In order to conduct research and analysis on the construction of application-oriented undergraduate data science and big data technology courses,the professional development characteristics of universities and enterprises should be taken into consideration,the development trend of the big data industry should be scrutinized,and professional application-oriented talents should be cultivated in line with job requirements.This paper expounds the demand for capacity-building professional development in application-oriented undergraduate data science and big data technology courses,conducts research and analysis on the current situation of professional development,and puts forward strategies in hope to provide reference for capacity-building professional development.
文摘The journal Genomics, Proteomics ＆ Bioinformatics （GPB） is now inviting submissions for a special issue （to be published in the summer of 2018） on the topic of＂Big data in brain science＂.
文摘The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. One paper on Cloud Computing published in Vol. 18, Issue. 1, 2013, has been ranked the top of IEEE download list continuously for five months：
文摘The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. One paper on Cloud Computing published in Vol. 18, Issue 1, 2013, has been ranked No. 1 of IEEE download list continuously for five months： http：//ieeexplore.ieee.org/xpl/browsePopular.jsp？topArticlesDate=August＋2013.
基金National Social Science Foundation of China--Research on the Hybrid Network for Scientific Structure Analysis(Grant No.19XTQ012)。
文摘The value of big data in science of science for knowledge discovery is that it can reveal deeper information and knowledge, promote knowledge integration in the whole process of scientific research, guide interdisciplinary integration, and provide new ideas and new methods for knowledge discovery research. This paper discusses the value and role of big data in science of science in knowledge discovery from five aspects, including exploring the laws of scientific research, revealing scientific structure, analyzing scientific research activities, supporting technical recognition and prediction, and serving science and technology evaluation.
文摘Science and Technology(S&T)evaluation plays a baton role in developing science and technology innovation.However,traditional S&T evaluation indicators and methods are difficult to apply effectively in S&T evaluation practice.This paper analyzes the transformation of the S&T evaluation paradigm in the digital environment.Theories,methods,and tools of S&T evaluation research are continuously innovated and optimized;big data becomes the driving force of S&T evaluation development;the role played by S&T evaluation is shifting from a provider of statistical data and information to a participant in S&T decision-making activities.S&T evaluation research should focus on improving data retrieval and organization,knowledge mining and knowledge discovery,and intelligent evaluation models.Moreover,we suggest that scientists carry out S&T evaluation in agreement with the needs of S&T development:1)monitoring and sensing the development of science and technology in real-time with the help of emerging digital technologies;2)exploring solutions to major concerns such as technical project management mechanisms,utilizing advanced data science and digital technologies to identify important scientific frontiers,and leveraging big data in science of science to reveal patterns and characteristics of scientific structures and activities;3)carrying out problem-oriented evaluation research practice focused on four aspects,including intelligent project evaluation,evaluation of the critical technology competitiveness,talent assessment,and diagnostic evaluation of the research entity competitiveness.
