Research on the Construction of Application-Oriented Undergraduate Data Science and Big Data Technology Courses

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.

Lone Geniuses or One among Many?An Explorative Study of Contemporary Highly Cited Researchers

Purpose:The ranking lists of highly cited researchers receive much public attention.In common interpretations,highly cited researchers are perceived to have made extraordinary contributions to science.Thus,the metrics of highly cited researchers are often linked to notions of breakthroughs,scientific excellence,and lone geniuses.Design/methodology/approach:In this study,we analyze a sample of individuals who appear on Clarivate Analytics’Highly Cited Researchers list.The main purpose is to juxtapose the characteristics of their research performance against the claim that the list captures a small fraction of the researcher population that contributes disproportionately to extending the frontier and gaining—on behalf of society—knowledge and innovations that make the world healthier,richer,sustainable,and more secure.Findings:The study reveals that the highly cited articles of the selected individuals generally have a very large number of authors.Thus,these papers seldom represent individual contributions but rather are the result of large collective research efforts conducted in research consortia.This challenges the common perception of highly cited researchers as individual geniuses who can be singled out for their extraordinary contributions.Moreover,the study indicates that a few of the individuals have not even contributed to highly cited original research but rather to reviews or clinical guidelines.Finally,the large number of authors of the papers implies that the ranking list is very sensitive to the specific method used for allocating papers and citations to individuals.In the"whole count"methodology applied by Clarivate Analytics,each author gets full credit of the papers regardless of the number of additional co-authors.The study shows that the ranking list would look very different using an alternative fractionalised methodology.Research limitations:The study is based on a limited part of the total population of highly cited researchers.Practical implications:It is concluded that"excellence"understood as highly cited encompasses very different types of research and researchers of which many do not fit with dominant preconceptions.Originality/value:The study develops further knowledge on highly cited researchers,addressing questions such as who becomes highly cited and the type of research that benefits by defining excellence in terms of citation scores and specific counting methods.

The Road to Self-Reliance of the First French Atomic Bomb

After World War II,the choice of the plutonium bomb as the technology roadmap for the first French atomic bomb was not a military issue,but rather one guided by civilian nuclear technology policy.After consideration of the amount of uranium to be mined,technical reserves,and the financial situation,the civilian nuclear energy project of the Commissariatàl’énergie Atomique(CEA)was based on plutonium and natural uranium as the fissile materials,which indirectly provided enough plutonium for the future development of a nuclear weapon.When the Fourth Republic decided to develop the atomic bomb,a“Common Core”was established with the CEA,a public institution,as the lead,assisted by the military.Faced by the US embargo of nuclear weapons technology,the co-existence of civilian and military branches and their collaboration to some degree in the CEA not only made it a civilian-military complex,but also facilitated breakthroughs in the core technologies of implosion,the plutonium core,the tamper,and the neutron source.The success of the first French nuclear weapons test on February 13,1960,announced that France was on its way to becoming self-reliant in the military use of nuclear science.

Big data analytics and big data science:a survey

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.

Call for Papers Special Issue on"Big Data in Brain Science"

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＂.

Call for Papers Special Issue of Tsinghua Science and Technology on Cloud Computing and Big Data

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：

Call for Papers Special Issue of Tsinghua Science and Technology on Cloud Computing and Big Data

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.

The scientific applications of big data in science of science

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.

New directions of digitally driven S&T evaluation

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.