Data journalism， also named data-driven journalism， is the convergence of traditional journalism industry and information technology. In this Web 3.0 era， the ways of using data become flexible and diverse， which makes journalism give birth to brand new reporting style. With the popularization of internet and mobile terminals， ordinary people， who used to contact much traditional journalism， are now likely to be immersed in data journalism， thus being significantly influenced.

The information people accepted is dynamic instead of static.

Browsing newspapers and magazines， or opening a news app in the phone， we can easily be informed of “what happened at some moment”. However， to have clear and comprehensive understanding of a specific event， knowing the process is essential. In the past， to establish a process model， people plunged into newspapers and periodicals， searching fragmented and static news， which was very complicated and inconvenient. Nowadays， data journalism provides people with websites that have motion charts containing information during a specific period of time instead of at a fixed time. A case in point is a report about Arab Spring in the website of the Guardian. Viewers can drag the time axis， click the labels and select areas with mouse and thus watching corresponding news as well as related links emerge in the motion chart. Obviously， such dynamic reporting way provides readers with more information and leaves a deeper impression than plain text and static pictures do.

Data journalism can even portray the process that people are not aware of. As information explodes， rumors frequently occur in internet. For instance， “retrograding female driver hit the bus in Chongqing”， “a take-out deliverer cried for stolen food”. Usually， people think refutations need relatively long time to appear. However， contrary to common sense， data journalism， based on accurate data analyses， proves that rumor-against information occurs soon after the wrong message released. Through visual dynamic graph， data journalism makes a difference in helping people figure out obscure processes.

Since a certain process contains abundant information and clues， data journalism can provide more accurate predictions. During the national holiday in 2013， in Sichuan province， Jiuzhaigou retained a large number of tourists. Nowadays such large-scale retentions can be avoided because data journalism， according to the big data in this respect， can report in advance in which specific time period， how many people from which places to Jiuzhaigou. As data journalism fuses with financial news， entertainment news， as well as medical news， people immersed in them are able to forecast financial market， booking office and the spread of epidemics. Powerful forecasting functions brought by big data absolutely make todays news more valuable and more advisable.

Journalism employment has tremendous variation.

In big data era， flourishing data news demands journalists become inter-disciplinary talents. Not only do they need the skills that traditional journalists have， but also have to master data gathering， data analyzing， data manipulating， as well as data visualizing. Such a tendency gives birth to great opportunities but disturbs some individuals.

The premise of obtaining abilities mentioned above is to have adequate “data thinking”， which belongs to scientific thinking. Consequently， graduates of science and engineering specialty， who have data thinking potential， are on the great march to journalism industry. Such circumstance was rare before big data era when journalism industry is mainly occupied with individuals majoring liberal arts.

However， to some degree， graduates majoring in journalism are overwhelmed by booming data news. Most universities and colleges dont open course about data for students majoring in journalism. Since data journalism lays more emphases on data processing， those graduates seem hard to get the upper hand in practical work. Some professors teaching journalism realized such problems， advising their students to cultivate “data thinking” and expand knowledge about other subjects， instead of only studying traditional journalism skills.

In short， thriving data journalism greatly increases the job competition in the news industry. In pace with this， outstanding talents coming out from fierce competition will surge into journalism industry.

Public interests are better defended.

During 2012 to 2018， 77 works won Data Journalism Award. Among them， 21 works concentrate on politics， with particular emphasis on political elections and political transparency. 10 works are crime-themed and 9 works lay emphasis on society. These reports reveal the hidden harm to public interests behind the social structure， or show loopholes in the rule of law in violent crimes and economic crimes， aiming at exposing contradictions to arouse social concern and promoting the state to improve or make up for the legal protection of public order and public interests.

Though traditional journalism never ceases defending public interests， it cant provide concrete evidence like concise statistics， on which data news is based. Data news relies on mature information processing technology to guarantee the accumulation and analysis of factual data. It breaks the attention cycle of traditional news， achieving long-term tracking， which effectively maintains the attention of social issues. For instance， in 2014， many immigrants seeking refuge in Europe died. Most media didnt pay attention to the problem until a massive immigration tragedy caused them to organize the whole long news cycle， which was inefficient and time-consuming， while some data news Data news created a comprehensive and reliable database on migrant deaths and continued to track European immigration policies， thus prompting the solution of the problem immediately.

Journalism ethics is being challenged.

Each coin has two sides. Despite remarkable benefits， data journalism increases two kinds of infringement risks.

Right of privacy is more likely to be infringed. To offer personalized news， data journalism inevitably searches for readers relatively private information. News producers can obtain these data through mining， exchanging or purchasing， and even make them into public news. Though a majority of people are reluctant to open their private data to the public， news organizations can make use of the information without permission of readers. The typical event illustrating this problem is that Facebook， a rally point of data news， has revealed 50 millions users private data in the past few years.

Flourishing data news also puts threat to the copyright of journalism works. Some news aggregation platforms， produce data news through collecting， re-editing， composing or decomposing， and then directionally push them to the public. In this process， these platforms often steal directly， or infringe the copyright of the original news works by jumping links or blurring the origin deliberately. Such platforms， like Headlines Today， dont produce news itself at all， making other source media become their “free workers”.

Data journalism is a double-edged sword， contributing to thriving of data epoch， also threatening status quo. Living in the new environment brought by data journalism， every individual ought to cultivate data literacy and bear basic ethics of journalism in mind.

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【作者簡介】楊瑜潤，暨南大學(xué)國際學(xué)院。