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Digital Transformation of Academic Journal Editing and Publication in Big Data Era

2016-03-28 19:28:56LINShiping
重慶與世界(教師發(fā)展版) 2016年6期
關(guān)鍵詞:數(shù)據(jù)化云計算物聯(lián)網(wǎng)

LIN Shi-ping

(Journal Editorial Department of Southwest University of Political Science and Law,Chongqing 401120,China)

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Digital Transformation of Academic Journal Editing and Publication in Big Data Era

LIN Shi-ping

(Journal Editorial Department of Southwest University of Political Science and Law,Chongqing 401120,China)

Abstract:The era of big data is coming,and compared with the age of no data and small data,journal’s editing and publishing industry will face a new challenge evitably,but it also brings new opportunities. The greatest opportunity is the transformation of working mode and mode of thinking. Therefore,the transformation of digitalized publishing to data-based publishing has become the trend of our times. Industrial upgrading,discovery and excavation of high quality articles from the data,more accurate positioning and services will become the top priority of editing and publishing.

Key words:big data; digitalization; cloud computing; Internet of things

Citation format:LIN Shi-ping.Digital Transformation of Academic Journal Editing and Publication in Big Data Era[J].The World and Chongqing,2016(6):110-114.

The year of 2013 is regarded as the first year of Big Data in China. In March 2013,the National People’s Congress,Mr. Zheng jie,NPC representative,general manager of China mobile in Anhui Province,indicated in his proposal that big data management needs support from national strategy,and it must rely on the government,enterprises and society to work together in forming large force of data management,and he proposed that big data should rise to national strategy and to build “Data China”.

In the intellectual community,big data technology is listed as one of revolutionary changes tied for the quantum computing. Mr. Fang Xingbin,fomer president of Beijing university of Post and Telecommunications,addressed before resignation to the students’ graduation ceremony that modern times is a society of knowledge explosion,and is the age of new knowledge and new technology emerging endlessly. “Quantum calculation,3-d printing,automatic content recognition,automatic driving,natural language questions and answers,text to speech translator,big data,NFC (near distance wireless communication) pay,gesture recognition,Internet security,cloud security,advanced persistent threat (APT),etc.,are waiting for us to explore,and you need to select and master the knowledge.”

The strength of big data is to reflect through mining and analysis. Big data era in editing and publishing industry is really coming,which will bring profound influence on thinking and working style of journal editors. The editing and publication of the digital transformation of our discussion in the past will face a new topic,namely the editing and publication of digital transformation. This paper aimed to give some further discussion to arise attention.

1Big data,a topic of the times

1.1 The origin of the term “big data”

The origin of the term “big data” can be traced back to the apache org (server side software development organization),open source project Nutch (open source,cross-platform application software Java implementation of search engine). At that time,the big data used to describe the need to update the network search index and batch processing or analysis of a large number of data sets. As Google Map Reduce (c++ programming tools) and the Google File System (GFS,Google File System),big data is no longer just used to describe a large amount of data,and it also covered the speed of data processing.

Big data is not only refers to the data,in fact it is a revolutionary technology,the strategic significance of technology is not the master of the large data information,but in the meaning of the specialized data processing of these meaningful data. Big data,or huge amounts of data,at least,is at PB level. It involves huge amounts of data size which is too big to capture,manage,process,and finish becoming more positive purpose information through the current mainstream software tools in a reasonable time to help enterprise management decision.

1.2 The use of big data

With the progress of the IT hardware and software technology,Google has made big data transformation as the main source of value; Retail company sells its products through tracking and analysis for more marketing opportunities; it not only can put sensors in the plane engine,the engine of life cycle,but also at the same time can be predictive maintenance,etc. The data warehouse,data security,data analysis,data mining,and so on,around big data by using the commercial value gradually become a focus of the IT industry to profit.

The U.S. government has regarded big data as the future of new oil. “In 2011,in its report to President Obama and congress the advisory committee of science and technology to the President of the United States,for the first time they put forward the strategy of big data from the national development level. In 2011,McKinsey & company launched a study under the big data: the forefront of innovation,competition and productivity ”. On March 29,2012,Obama announced it would put more than $200 million immediately launcheing the “Big Data and Research Development Plan” (Big Data Research and Development Initiative).

1.3 The characteristics of big data

4V characteristics: Volume,and there is enormous data capacity Volume. In the 1990s,the personal computer hard disk is easily measured in megabytes (MB),then increased to GB,now has risen to the level of TB. But the era of big data will jump to the PB level; Variety,there are various data types. Such as web logs,video,picture,location,etc. Value,there is low density in vaule,and the commercial value is high. In video,for example,the process of continuous uninterrupted monitoring data can be useful for only one or two seconds; besides,there are Velocity and the laws of one second. Finally there are fundamental differences between the traditional data mining techniques.

After cloud computing and Internet of things,the information industry is faced with a disruptive technological change: the “big data”. Famous futurist Alvin Toffler (Alvin Toffler),as early as in 1980,had written in his book The Third Wave that if the IBM host up to the information revolution,the “big data” is the third wave of reality. As early as in 1980,the Third Wave of the big data enthusiastically was praised as “the third wave of reality”.

In fact,the IT industry in our country and the legal,economic and other scholars in the field of many years ago began to focus on big data technology. The Beijing municipal commission of economy and information technology instruction,Beijing economic and technological development zone and cloud base jointly hosted the “cloud of the world 2011” conference,first named “cloud,big data,” as a subject at the venue.

Big data technology authority figure is Viktor Meyer who is a professor at the University of Oxford- Schonberg. He pointed out that “big data is a big topic,also is the topic of this year and is very popular” in 2012 in Beijing.

Viktor Meyer-Schonburg pointed out: “Google and Apple,they can use this approach to the management of the business locations,and give their smartphone to achieve specific positioning function,even when the GPS cannot work. A U.S. company for hundreds and thousands of individual commercial credit reporting company also can use these data to see if it can have one timely treatment,finally it can also predict data related to medication adherence. Retail companies in the United States will also be able to put his trading data to predict a female customer pregnancy,and orientate them by looking at the habit of users to buy.”

Big data technology has profoundly affected our life,work and the way of thinking. Recently,“prism door event” exposed in the United States and snowden pursuit by the U.S. government caused worldwide concern,and also let big data technology to boom,and with the development of cloud computing and the advent of the era of big data,people produce huge amounts of data will be more and more in the Internet,such as E-mail,personal files,the credit card information,geographic location,personal scheduling,ebooks,photo,etc.,and we also enjoy the welfare of the cloud computing,but the emergence of the prism plan gives hidden danger and skeptical attitude in information security. In fact,the founder of (Wiki Leaks) who was arrested in London in 2010 use a large amount of data to reveal the unethical behavior of the government and company.

2 The transformation of editing and publishing from digitalization to data-based

In the United States,there is a widespread proverb,that is: “Every one must use data to speak except God” (a famous American quality expert,Edward Deming’s words). The United States is a country worship of data,and likes to talk with data. In many of the classic theory and the theory of communication,it is derived from quantitative analysis of the empirical school. Human nature is observation,analysis and measurement,so it can say that the essence of the world’s data,the era of big data will open a major transformation. At present,the cloud computing,cloud living,cloud publishing is ascendant in China. In fact,cloud publishing and big data are on the same proposition. Big data presented problems,while cloud computing is the method. Cloud computing and big data will inject new vigor and vitality to the publishing industry.

Digital publishing has already been promoted to the national strategic level,and the Chinese government vigorously promote the digital publishing periodicals. But the rapid development of science and technology tells us that only digitalization can’t keep up with the pace of the Times,data-based publishing represents the future,which will have a significant impact upon governance mode,enterprise’s decision-making,organization and business process,and to individual way of life.

In the era of big data,the transformation of editing thinking will be faced with the following four aspects: one is on the research methods. The data transformation from the random sampling to all,namely replacing commonly used sampling methods; The second is transformation from the accurate data to the general direction,namely,focusing on the mix of unstructured data. In the era of small data,the conclusion of any data error can lead to serious errors,but in big data era,due to the large scale of data as a whole,the individual data error will not affect the overall conclusion and forecast. The third is transformation from causal relationship pursuit to relevant relationship quest. Human nature is to explore the causes of things,but in the era of big data,the researchers will no longer ask why,but show what it is,and let the data speak. The forth is transformation from intuitive prediction to prediction based upon big data,which is the prediction by the mathematical algorithm to huge amounts of data analysis. Some language text is in the process of digital transition,so,in the field of social science and humanities research,data is becoming more important than experience.

Digitalization is just the basic requirement of information society,and the big data era is the advanced stage of the information society. For periodical publishing,digitalization greatly improved the transmission efficiency and improved the editing and publication environment and conditions,but big data may provide opportunity for industry upgrading. Especially in the field of humanities and social sciences periodicals publishing,for editors used to rational judgment,and the data analysis of small data is based on the investigation and study analysis,emphasizing the significance and role of data,will be very beneficial to improve the editing and publishing work currently.

3 New opportunities: how we edit in the big data age

All technological progress of mankind will have a significant impact in related fields such as the papermaking by CAI Lun in Western Han dynasty helps spreading books,and the influence of German Gutenberg bronze printing on the spread of Bible,which even leads to religious revolution. The editing and publishing work in the era of big data are also in the face of the challenge and a new development opportunity.

3.1 Industrial upgrading

In the era of big data,editing and publication workers’ skills and the tools used are likely to upgrade,which is a great leap forward compared with the traditional judgment and manual experience or half manual operation. In the era of big data,journal publishing is likely to further developed and expanded. In terms of resource reorganization and structural optimization,at present,under the condition of insufficient data,periodical publishing unit personnel,capital,sites,distribution channels,print run,profits,funded projects,as well as the audience,author distribution and utilization of literature resources can’t very well reflect in time through the data,and if you can achieve the data and integration timely,it will be able to show well the present development situation and prospects of the industry,so that the management and decision-making body quickly take effective measures to improve. For example,one management organization subordinate to the Ministry of Education in 2012 conducted a questionnaire concerning the journal editorial department system reform. If in the era of big data,you can focus on analysis of journal editors in the paper,the network community (BBS) to speak,discuss and chat,the network diary,blogs,video,photographs,and so on various aspects of the related data,the conclusion and forecast will be more efficient and more real than the questionnaire.

3.2 Finding high quality articles from the data

In terms of academic journal or editorial office,due to the limited human and financial resources,at present,there are few statistics about the utilization of manuscript,output of scientific research institutions,and the authors’ distribution and status,as well as download reading after publication. Some big data platform,such as CNKI digital journals and Wanfang,Longyuan do offer a statistical analysis about publication,but the use of these tools is unsatisfactory,and more importantly,they can’t provide forecasting service on hot topics and output. The editing subject plan is basically through the traditional manual or semi-manual mode by experience. This leads to our editorial published behavior belongs to extensive original business model.

The original business model would be very unfavorable to industry competition. If good quality article depends on personal interests of editors and good luck,it will eventually kill off our editorial publishing. In the information age,publishing,as the content industry,is completely necessary to occupy information media through the professional service,giving full play to the advantages of industry. Instead of being covered by so called “We Media”.

Through scientific research institutes,colleges and universities and other scientific research paper output,disciplinary subject keywords,academic words,search of academic trend chart analysis,editors can see in time the academic resources distribution and changes of visual graphics,and forecast the output institutions and scholars,and guide them to the targeted editing. For free contributions,editors can also judge the manuscript of innovative and quality through the relevant data.

3.3 More accurate positioning and service

Personalized analysis of big data includes the people’s behavior,position,preferences and even psychological and physiological data. The service object of Journals published is people,so we can be targeted to forecast the readers expect the topic through software.

Then,the pertinence and efficiency of the selected topic and manuscript can be strengthened.

Through big data software,periodical distribution and active readers can be seen timely,journal editing can be targeted for journal promotion,content delivery and other services,through RSS aggregation content customization,better provide content service for readers. Editorial office can also provide special literature retrieval service for readers,and through big data analysis to predict the topic to the author,as a contributor and guidelines.

3.4 Improve periodical evaluation system

At present,the domestic periodical evaluation system is based on three core journals as the standard,namely,Beijing university of Chinese core journals of library development,CSCD developed literature information center,Chinese academy of sciences,the Chinese science citation database,and Nanjing university of Chinese academy of social sciences research evaluation center of CSSCI,namely the issue of “C”. However,even if the core journals are not misused,this evaluation standard published every two years must be obvious deficiencies. If the journal publishing unit can timely grasp journal evaluation and utilization by the readers,and even of a single paper and paper details specific view of feedback,it will be closer to the real evaluation of periodical readers,which can also guide the social adjustment editorial policy or strategy,and publishing plan for better arrangement more timely.

Based on the “l(fā)et the data speak”,thesis evaluation or periodical evaluation system is more scientific,reasonable and persuasive.

4 Conclusion

Big data era has profound and far-reaching influence on editing and publication work. Due to the progress of science and technology,human beings inventions change the human life,work and the way of thinking. Any major technological change inevitably brings the innovation of ideas. Such as mobile phone communication technology makes the world into a “global village”,from the reality to the virtual human relationships,but interactions change does not affect the freedom of the human spirit,on the contrary,it achieves a greater level of freedom. Editing job as a study of people,although the traditional concept of “content is king” has not been rewritten,but the concept of “channel is king” is also positive. In the process of journal editing and publication,transformation from digitalization to big data will become the forefront of industry competition and the source of the system and mechanism innovation. The possession and use of big data can form a new round of industry competition,especially in the periodical publishing marketization and the transformation of enterprise,big data will strengthen the power of the publishing “tool”. Therefore,in the era of big data,it is necessary for editing personnel to keep pace with the times,to understand and grasp the big data technology and to make full use of the new technology to promise the periodical industry a better tomorrow.

References:

[1]AASTOCKS.com Limited. National People’s Congress member Zheng jie’s suggestion on that big data should rise to national strategy and we should build “data China”[EB/OL].[2013-03-05].http://cj.gw.com.cn/news/news/2013/0305/200000128873.shtml.

[2]FANG B X. M-tips before graduation from the principal of Beijing University of post & telecommunications,life pursuit of “six good”: Principal Fang Binxin’s (microblogging) speech at the class of 2013 undergraduate graduation ceremony[EB/OL].[2013-03-27].http://news.sina.com.cn/c/2013-06-27/115827512910.shtml.

[3]Journalist of the journal. In Big Data Era,How the Media Transform[J]. Editors’ Friend,2013(6): 6.

[4]ZHENG W L.Informatization construction[J]. 2013(1):10-13.

[5]China’s software development network (CSDN). Viktor Mayer-Schonberger,professor of University of Oxford: vaule brings by Big Data[EB/OL].[2015-05-20] http://articles.csdn.net/plus/view.php?aid=2812717.

[6]China Cloud Network. Viktor Mayer-Schonberger: Re-research on the definition of Big Data[EB/OL].[2012-12-12]. http://www.china-cloud.com/yunzixun/yunjisuanxinwen/20121212_16737.html

[7]JI H. Reveal the prism program behind the technology[EB/OL].[2013-06-26]. http://www.csdn.net/article/2013-06-26/2816002-the-technology-behind-the-prism.

[8]ZHANG G M. The thinking and enlightenment of the era of large data: on reading Xu Zipei’s Big Da ta [J]. Journal of water conservancy,2012(9): 40.

[9]ZHAO G D. “big data” thematic analysis:the coming era of big data[R]. Sinolink securities,2012.

(責(zé)任編輯楊梅梅)

作者簡介:林士平(1963—),副編審,博士研究生,研究方向:編輯出版。

doi:【編輯與出版】10.13769/j.cnki.cn50-1011/d.2016.06.026

中圖分類號:G23

文獻(xiàn)標(biāo)識碼:A

文章編號:1007-7111(2016)06-0110-05

大數(shù)據(jù)時代期刊編輯出版的數(shù)據(jù)化轉(zhuǎn)型

林士平

(西南政法大學(xué)期刊編輯部,重慶401120)

摘要:大數(shù)據(jù)時代即將來臨,與無數(shù)據(jù)和小數(shù)據(jù)時代相比,期刊編輯出版業(yè)必將面臨新的挑戰(zhàn),但也帶來新的機(jī)遇。最大的機(jī)遇就是工作方式和思維方式的轉(zhuǎn)型。因此,由編輯出版數(shù)字化向數(shù)據(jù)化的轉(zhuǎn)型便成為時代的潮流。產(chǎn)業(yè)升級、從數(shù)據(jù)中發(fā)現(xiàn)和挖掘優(yōu)質(zhì)稿源、更加準(zhǔn)確的定位和服務(wù)將成為編輯出版業(yè)的首選目標(biāo)。

關(guān)鍵詞:大數(shù)據(jù);數(shù)據(jù)化;云計算;物聯(lián)網(wǎng)

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