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This article will explain in detail how to make big data an important tool for dealing with emergencies. The content of the article is of high quality, so the editor shares it for you as a reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

In recent years, emergencies occur frequently, which have a great impact on economic and social development, and the uncertainty of emergencies brings great challenges to emergency management. The emergence of big data brings new changes and new ideas to the handling of emergencies. The combination of emergency management and big data subverts the traditional concept and thinking of emergency management, promotes the digitization and technicalization of emergency management, and enhances the initiative and predictability of emergency management. it greatly improves the government's emergency management ability and provides reference for emergency decision-making.

The Application and value of big data in dealing with Emergency

The Evolution of unexpected events and the value of big data

Emergencies refer to natural disasters, accidents, public health events and social security incidents that occur suddenly, cause or may cause serious social harm, and need to be dealt with by emergency measures. In the network and information age, the occurrence and development of emergencies show a more complex and changeable situation. In basic concept, network emergency is not only the extension of emergency in the network, but also expands the scope of emergency in cyberspace and enriches the meaning of emergency. Network security accidents, information leakage, network sudden public opinion, network terrorism and so on themselves belong to the category of emergencies, so that emergencies have more network-related characteristics. In the form of expression, the occurrence and development of emergencies under the background of traditional media have certain limitations, and have strong controllability and plasticity. However, the emergency under the background of the network has more uncertainty, and the network has become the inducer and booster of the emergency, which speeds up the spread and spread of the emergency, and the influence of the emergency increases exponentially. And it is difficult to effectively prevent, control and predict.

Big data, as its name implies, is a collection of a large amount of data, a massive, high growth rate and diversified information asset with stronger decision-making power, insight and process optimization ability. it is necessary to use advanced technology and tools to realize the whole chain of data processing, dig out valuable information and realize data "value-added". The most important role of big data lies in semantic engine, data management, data mining, visual analysis and predictive analysis, which makes up for the shortcomings and defects of traditional emergency handling methods. an emergency handling mechanism supported by data is established, which injects vitality into emergency handling, helps emergency handling to be more accurate and efficient, and guides emergency management to make more scientific decisions. In this epidemic prevention and control war, big data played an important role in epidemic situation research, prevention and control deployment, transmission path analysis, personnel mobility monitoring, and enterprise resumption of work and production.

Big data innovates the concept and mode of emergency management

With the development of information and communication technology and Internet technology, big data's technology and application came into being, brought about a change in information and data, and subverted the mode and method of emergency handling. Emergency handling began to change from passive to active, from afterwards to prevention.

First of all, the change of emergency management concept. In the face of the massive data generated by various industries, fields and events in the information age, it is obviously difficult to find, track and deal with emergencies by relying on the traditional data statistics and analysis methods. Big data's technology builds a bridge between emergencies and emergency management, and provides new ideas and ideas for government departments to deal with emergencies and strengthen emergency management. The objectivity of data and the universality of technology provide more in-depth analysis, faster early warning and more accurate prediction for emergency management. Relying on data and technical decision-making is increasingly becoming the mainstream of emergency handling in the future.

Secondly, the transformation of the way to deal with emergencies. The most important feature of the combination of big data and emergency management is to enable emergency handling. From the context of historical development, from the massive data, with the help of big data analysis technology, found the law of the development of events and signs of tendency, so as to capture the subtle changes before the occurrence of emergencies. This will greatly enhance the predictability of emergency management, promote the transformation of emergency handling from "post" to "front", and enhance the timeliness and scientificalness of dealing with emergencies in a timely and scientific manner. truly achieve emergency awareness in advance, scientific prevention and control, trend prediction, and minimize the crisis.

Big data broadens the data sources of emergency management

The typical feature of the information age is the information explosion, and earth-shaking changes have taken place in information production and data transmission. With the development of mobile Internet, the wide application of new media, the arrival of the Internet of everything, the increasing popularity of artificial intelligence and the development and utilization of bioinformation technology, the amount of data has increased geometrically, which has greatly expanded the data sources of emergencies and broadened the boundaries of emergency management. According to a report released by IDC, China's data circle accounted for 23.4% of the global data circle in 2018, reaching 7.6ZB, and is expected to account for 27.8% of the global data circle by 2025, increasing to 48.6ZB, making it the largest data circle in the world.

At the macro level, the data and information obtained by the government, industry, institutions and organizations in response to emergencies is no longer limited to television, radio, news media and internal government data. Through social platforms, short videos, data centers and big data technologies such as information awareness and association aggregation, we can collect and analyze information from multiple levels and on a large scale, form data drawings and portraits of emergencies, accurately locate and predict the occurrence, development and future changes of emergencies, and provide a standardized, systematic and systematic disposal mechanism for emergencies.

At the micro level, individual behavior is also the focus of emergency management, and the relevant data and information are the objects of emergency data collection. In the information age, individual behavior or group behavior can be digitized. Through the analysis of individual and group behavior patterns, we can explore the individual characteristics and functions behind unexpected events, as well as the behavior of groups composed of many individuals with the same or similar views, so as to predict the possible outbreak of group events. In fact, in many emergencies, opinion leaders have played a key role in voice, leadership and climate formation. In addition, the big data analysis of individuals and groups can also provide help and guidance for emergency response. For example, in earthquake, flood and other disaster events, the voice of many individuals and groups is the focus of emergency work, the collection of relevant data undoubtedly provides great help for event disposal.

Emergencies involve many fields and involve numerous objects, so it is difficult to effectively carry out relevant response, disposal and prediction work without a large amount of data and information support. The increase of the number of sources and the growth of the amount of data provide a broader field of vision and space for emergency management and decision-making, which helps the decision-making analysis and emergency handling of emergencies. For example, during the outbreak of COVID-19, through the collection and analysis of population mobile positioning data, the accurate detection and prediction of personnel mobility provided technical support for epidemic prevention and control and reduced decision-making mistakes caused by lack of information.

Big data improves the early warning ability of emergencies

In their best-selling book, the era of big data: the Great change in Life, work and thinking, Mayer Sheenberg and Kukeye put forward: "the core of big data is prediction. It is to apply mathematical algorithms to vast amounts of data to predict the possibility of things happening." Google has successfully predicted the outbreak of influenza A H1N1 through big data analysis. During the epidemic of COVID-19, big data technology was widely used in the process of personnel flow, itinerary query, epidemic map, data statistics, resource allocation, etc., which became a bright spot of epidemic prevention and control and provided great help for the government's scientific decision-making. The role of big data technology in emergency prediction has been widely recognized and gradually applied to natural disasters, accident disasters, public health events and social security events.

In the previous emergency prediction, due to the lack of the ability to calculate and analyze a large number of data, people can only rely on knowledge summary, experimental observation and experience prediction, and the results are random and individual differences. Big data technology can effectively realize the full aggregation of historical data and real-time data, comprehensively analyze the data from time, attribute, emotion and other dimensions, find out the relevance behind the data, and mine the potential value of the data. in order to get the trend of the development of the event. Big data's role in emergency early warning and monitoring is mainly reflected in two aspects. In the subjective aspect, big data is used to summarize the occurrence and development of past emergencies, find the rules, and compare them with real-time data to determine the probability and direction of emergencies, so as to enhance the predictability and disposition of emergencies and improve the ability of the government to deal with emergencies. In the objective aspect, big data's technology can overcome the unfavorable factors such as high tension, high intensity and time pressure in emergency crisis situations, and make objective analysis and prediction which is not based on personal will and experience judgment.

Big data's problems in dealing with emergencies

Big data is lack of operational thinking, and the phenomenon of data isolated island needs to be solved.

The occurrence of emergencies is the result of a variety of factors, with a high degree of abruptness, urgency and uncertainty, resulting in a greater social impact. In recent years, factory deflagration, traffic accidents, ground collapse and public health and safety incidents have exposed the shortcomings and defects of emergency management in our country.

At present, the application of big data in emergency handling has not been popularized and given enough attention. The old thinking habit of "relying on manpower" and some institutional obstacles still exist, and big data's concept has not yet become the mainstream. First of all, in the handling of emergencies, the government's ability to collect and use data and information still needs to be improved. The phenomenon of "emphasizing results, neglecting prediction" and "emphasizing response and neglecting analysis" is widespread. As a result, big data's role in emergency handling has not been fully excavated and demonstrated. Secondly, various departments in our country have their own functions in dealing with emergencies, and they have not done enough in data exchange and information sharing, which has given rise to "information barriers" and "data isolated islands", that is, data cannot be circulated among various departments. lack of big data basis, it is difficult to carry out effective analysis and prediction, thus unable to make scientific decisions.

Big data's foundation is not perfect, and the database construction has a long way to go.

Although the types and scope of emergencies are increasing, there are still rules to follow, and historical data and existing data are the best examples. In order to do a good job in the prediction and prevention of emergencies, we must grasp the data of emergencies in various industries and fields, form an emergency database, and provide scientific support for emergency handling and emergency management. However, in China, the development and construction of big data is still in its infancy, and the emergency database needs to be promoted urgently.

First of all, historical data is an important basis for emergency management and forecasting, lack of historical data analysis, it is impossible to make a more comprehensive summary of a certain type or field of emergencies, let alone establish a forecasting model for deduction. Especially in the aspects of major production safety accidents and group incidents, some emergency management work ignores the analysis and research of historical data, which leads to similar incidents occurring from time to time and falling into a passive situation.

Secondly, the construction of emergency database is faced with two difficult problems. On the one hand, whether it is historical data or existing data, data collection and collection is a long-term and continuous project, which requires a large amount of investment. On the other hand, there is a lack of unified technical standards, data standards and interface standards in database development and construction, which leads to the lack of effective docking of inter-departmental systems and a great discount on data interconnection.

Unstructured data becomes a difficult problem, and data storage analysis is challenged.

Big data includes structured, semi-structured and unstructured data. Unstructured data refers to a kind of data with irregular or incomplete data structure, including a variety of office documents, audio and video, pictures, machine data, etc., accounting for more than 80% of the total data. Compared with structured data, unstructured data has the characteristics of various formats, high storage proportion and difficulty in processing.

With the development of Internet technology, the traditional relational and structured data is no longer the mainstream, and the proportion of unstructured data will become larger and larger. The spread of emergencies is becoming increasingly networked and video-based, resulting in a large number of unstructured data flooding the network. Emergency analysis and early warning based on big data analysis are facing the problem of unstructured data processing. First of all, the storage of a large amount of unstructured data consumes a lot of resources, and data storage will become a challenge. Secondly, it is not easy to deal with these "clunky" unstructured data, we are still unable to identify picture information quickly and accurately, and there is no effective means to extract video information.

In the face of the unstructured data which contains a lot of value, how to expand the storage capacity and improve the storage efficiency, carry on the "structured processing" of the "non-institutionalized data", and clearly construct the basic elements of emergencies. Establish an analysis and prediction model to assist decision-making to test the emergency management in big data era.

New technology and new business bring new changes, and multi-technology integration is imperative.

With the continuous emergence of new technologies and new services, emergency management and emergency management are also faced with more problems and challenges such as data collection and processing.

First, the types of data are numerous and complicated. The data generated by the new media represented by self-media and social media are complex, with different types and formats, and the structured and unstructured data are mixed. Some of the data seem to be disorganized and can be shown only after screening, filtering and cleaning, which brings great difficulties to data collection, classification, analysis and processing.

The second is the closure and encryption of data. Instant messaging tools such as Wechat, QQ, Zhihu and other circle groups have become important channels for the dissemination of information and the source of public opinion. The timeliness and efficiency of release are much higher than those of traditional news media. Many emergencies spread on these platforms at the first time, attracting the attention of the whole network. As the public pays more and more attention to privacy protection, encrypted data or non-public data will become the mainstream in the future and become more and more difficult to obtain. All kinds of encrypted chat tools, such as telegram, Bridgefy, Firechat and so on, are widely used in the anti-amendment storm in Hong Kong, which is the main way of information exchange, communication and collusion, which poses a great challenge to emergency management.

Third, the "dark net" data is boundless. Analysis shows that, compared with the "open network", the "dark network" accounts for more than 90% of the total network data, which is a veritable large database. However, the "dark net" is a "paradise" for cyber crime, drug trafficking, child pornography, assassination, selling national intelligence and improper financial services, and a dark place that is difficult to reach in a sudden emergency. In the future, multi-technology cooperation may be needed to deal with emergencies.

Suggestions on perfecting big data's analytical mechanism for dealing with emergencies

Bravely embrace big data and innovate the thinking of dealing with emergencies

General Secretary Xi Jinping stressed that big data should be used to raise the level of modernization of national governance. It is necessary to establish and improve big data's mechanism to assist scientific decision-making and social governance, promote the innovation of government management and social governance models, and achieve scientific government decision-making, accurate social governance, and high efficiency of public services. In the era of big data, emergency handling will rely more and more on a large number of effective data. The more and more comprehensive the data, the deeper the data mining and the more thorough the analysis, the more we can grasp the law of emergencies, find the signs of emergencies, make accurate predictions, and improve the efficiency of emergency management.

Government emergency management and disposal should actively embrace big data, implement big data's governance concept, establish big data's analytical thinking, strengthen big data's application practice, and give full play to big data's role and effectiveness in emergency response. It is necessary to change the thinking of emergency management, learn more, use more, learn and use data flexibly, and use big data to guide emergency handling. Strive to improve big data's application ability, master big data's basic concepts and analysis methods, and strengthen the ability of monitoring and early warning of emergencies, so as to "look at the future from big data."

Promote sharing and cooperation to improve the ability to deal with emergencies

Emergency handling focuses on multi-party participation and information linkage, and data circulation and sharing are very important. First of all, it is necessary to break down the data barrier and realize the data sharing and fusion. In recent years, China attaches great importance to the construction of emergency management system, and various departments have established emergency management platforms one after another, but the vertical and horizontal flow of data has been hindered because of departmental interests and technical standards and other factors, resulting in low data utilization. It is difficult to play big data's role in emergency management. Breaking down the information barrier and unblocking the data circulation channel is the key way to improve the ability to deal with emergencies. It is necessary to prevent government data and social data from becoming "zombie data", strive to solve the problems of "unwilling to share", "dare not share" and "cannot be shared", and promote the value-added and integrated application of data sharing from the aspects of ideology, management, system, law, and so on, so as to maximize big data's role in dealing with emergencies. For example, the health code implemented everywhere during the epidemic is a good proof of data sharing and service integration.

Secondly, it is necessary to strengthen the cooperation between government and enterprises and form a pattern of multi-party participation. In the information age, the main body of emergency handling should not be limited to government managers, but should mobilize the enthusiasm of enterprises, institutions and organizations, form a joint force of data, and provide staff for emergency handling. This requires that government-enterprise data can be effectively docked, give full play to the advantages of enterprises in technical support and data analysis, and provide reference for emergency decision-making. We can introduce third-party technical support units, purchase big data services, extensively carry out big data cooperation, and establish a long-term mechanism for big data analysis of government and enterprise emergencies. For example, the Office of the Central Cyber Security and Informatization Commission issued the Circular on doing a good job in personal Information Protection and using big data to support Joint Prevention and Control work on February 4, 2020, encouraging capable enterprises under the guidance of relevant departments. Big data is actively used to analyze and predict the flow of key groups such as confirmed diagnoses, suspects, and close contacts, so as to provide big data support for joint prevention and control work.

Establish big data Center to co-ordinate emergency management

With more and more emergencies, data flow is becoming more and more frequent, the trend of cross-regional linkage of emergencies is becoming more and more obvious, and the data relevance is becoming stronger and stronger. A small emergency that occurred somewhere may have been exposed for the first time in other places far away from it, spread all over the Internet and all over the country, and evolved into a regional or even national event. In order to better deal with emergencies and strengthen emergency management, we must break the regional boundaries of data and co-ordinate data management through the establishment of big data Center or big data platform.

The construction of big data center or data platform should meet two basic requirements. First, it can classify and process the data of different regions and different departments to form a national or regional "data lake". It is necessary to strengthen the intensive processing of data, so as to realize the circulation, transfer, analysis and processing of data across levels, regions, systems, departments and services, and improve the ability to perceive, predict and prevent emergencies. Second, it can allow the data to be open to the public, on the premise of ensuring that the data can be made public, protect the public's right to access information and help deal with emergencies. Especially in major emergencies, the realization of information disclosure can stabilize social mood, mobilize the enthusiasm of public participation, improve the flexibility of emergency management, and carry out more accurate regulation and control according to the development of the situation. In the prevention and control of COVID-19 's epidemic situation, the data disclosure of various data centers and information sharing platforms such as Xinhuanet's "COVID-19 epidemic latest data query and Service platform" and Dingxiangyuan's "Global novel coronavirus latest Real-time epidemic Map" have provided efficient and timely information for all sectors of society and played a key role in big data's fight against epidemic.

Comprehensive use of new technology to solve the problem of dealing with emergencies

The development of new technology and new business will bring about data changes, and the effective data available for emergency handling will be affected. Big data technology alone is difficult to meet the requirements of emergency handling in the future. General Secretary Xi Jinping pointed out in an important article "comprehensively improving the ability of prevention and control according to law and improving the national public health emergency management system" in Qiushi magazine that it is necessary to reform and improve the prevention, control and treatment system of major epidemic situations. We will encourage the use of digital technologies such as big data, artificial intelligence and cloud computing to play a better supporting role in epidemic surveillance and analysis, virus traceability, prevention and control, and resource allocation. Therefore, emergency handling should keep pace with the development and changes of the times and technology, constantly reform and improve the emergency management and disposal system, and make comprehensive use of modern information technology on the basis of big data's analysis mechanism to resolve related problems and challenges. we should improve the scientific, professional, intelligent and fine level of emergency management, promote the modernization of emergency management management system and management capability, and make our country become a scientific and technological power of emergency management.

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