# Volunteer Service Participation Emergency Management Information Collection Platform Based on Big Data Technology

Authors: Daqing Wang
Journal: Mathematical Problems in Engineering
 (2022)

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## Abstract

In order to fully integrate various emergency management information resources for volunteer service, the author proposes a volunteer service participation in emergency management information collection platform based on big data technology. Taking a municipal government as an example, the current situation of information integration in emergency management is investigated and studied, the needs of various departments are analyzed through interviews and questionnaires, and the problems existing in the government’s information integration are studied. It tries to build a scientific, reasonable, and operational government information integration model based on theories of government information disclosure, government emergency management, and metadata technology. The survey results show the following observation: In the survey results of “the reasons that affect the integration of emergency linkage information of a city government,” the first place is the poor information communication channels between departments, accounting for 22.7%; The second and the third are “administrative system restrictions” and “protection of the interests of the department,” accounting for 21.4% and 19.4%, respectively. It is worth noting that the technical problem of information management is also one of the important factors affecting the government’s emergency response management, accounting for 19.1%.Conclusion. This study analyzes the main shortcomings and reasons of the existing sharing models, so as to construct a reasonable information sharing work model.


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## Body

## 1. Introduction

The history of human development is a history of coping with challenges, overcoming disasters, and making continuous progress. With the development of human society today, the economy, society, and culture have achieved unprecedented prosperity. The increasing generalization and deepening of globalization and modernization have not only brought countless opportunities to human society but also created countless risks. Natural disasters caused by human beings ignoring environmental damage and demanding from nature savagely, it has become more and more frequent, and the economy, society, and nature have entered a stage in which various emergencies have higher probability, greater destructive power, and stronger influence [1]. In recent years, a series of emergencies such as earthquakes, tsunamis, floods, freezing, high temperature, and the spread of highly pathogenic infectious diseases have not only been much more than normal in the past but have also caused more and more serious harm to human life. From the general law of social development, when a country’s economy develops to a certain stage, it will enter a stage of frequent disasters and accidents with prominent contradictions based on social resources and institutional constraints. At this stage, it often corresponds to the period when the bottleneck constraints of social contradictions such as population, resources, environment, efficiency, and fairness are the most serious, and it is also a critical period in which social and economic imbalances, national psychological imbalances, and social ethics anomie are prone to occur [2]. At present, China is in an accelerated period of economic transition and social transformation, with the continuous deepening of industrialization and urbanization, the pressure caused by the rapid growth of society and economy is increasing, the deterioration of the natural ecological environment, and the cyclical changes in the activities of nature itself; this has led to the frequent occurrence of major natural disasters such as earthquakes, floods, droughts, hurricanes, and freezing of ice and snow in China in recent years, public health events such as SARS and highly pathogenic avian influenza frequently occur, and major criminal cases, foreign-related emergencies, mass violence, and political riots occur from time to time, accidents continue one after another [3].


## 2. Literature Review

Awajan et al. proposed the definition of “sustainable” community, based on the disaster reduction model, the reconstruction model, and the structural cognitive model and expounded on the connotation of “sustainability,” it is believed that the impact of sudden disaster events can be minimized through unified and coordinated organization and mobilization of the community public [4]. Lv and Li. proposed a community-based disaster reduction model, fully affirming the important role of the community in disaster reduction processing [5]. Guo studied the positive role of community participation in community disaster reduction work [6]. Tian, and others believe that the important role of volunteer organizations in urban community emergency management cannot be ignored, and the government departments should actively consider and provide an effective emergency participation mechanism [7]. Kaabar et al. Proposed a comprehensive urban community fire risk identification and assessment method, using a fire impact model to assess the risk factors affecting a given building fire [8]. Khan et al. studied the dynamic risk management model in the fast time-varying system, and constructed the framework of the emergency risk measurement model and risk decision model [9]. Ivanets et al. devised a simplified model for emergency risk management, and it is used to deal with the problem of too many treatment plans and risk sources in emergency risk analysis [10]. Yuan and Zhang studied the risk trust based on the total variation theory based on the trust research angle of emergency risk analysis [11]. Hannoun et al. used the accident risk assessment method in industry (ARAMIS) to analyze safety hazards, proposed an alternative protocol and method for risk reduction and reassessment, and used the odyssey marine accident to validate the proposed method’s effectiveness [12]. Huang et al. classified risk analysis, assessment methods, and techniques from the perspectives of qualitative, quantitative, and comprehensive (qualitative combined with quantitative, semi-quantitative), and finally achieved the effect of improving risk management capabilities [13]. Shamzhy et al. studied a diversification technique to analyze and predict the risk of regional maritime emergencies in the United States [14]. Hameed and Garcia-Zapirain proposed the uncertainty threat (RMS Probabilistic Terrorism) model of risk management schemes, which defined risk as a functional form; it is used for risk estimation under uncertainty of information [15]. The author mainly adopts the methods of theoretical research and questionnaire survey. In the elaboration of related concepts, theoretical research methods are mainly used, and a simple and concise elaboration of big data technology, emergency management theory, information integration demand theory, etc. The information and data related to this thesis of a city government department are used in the form of questionnaires, and the integrated application of emergency management information in a city is taken as a research case, under the background of big data, the problems, and reasons existing in the integration of emergency linkage management information for volunteer services in a city government are comprehensively expounded, which are used as the basis for the practice of this topic.


## 3. Research Methods

### 3.1. Overview of Government Emergency Management Theory and Practice

#### 3.1.1. Basic Theory of Emergency Management

Integrated emergency management system is a term commonly used in public safety management, or “Emergency Management Partnership” or called “All Agency Approach/All-agencies Approach” or “Integrated Approach”. When emergencies occur, representatives from different agencies, departments, and all levels of government are required to work together and cooperate with each other and decisions must be made quickly. If there is a lack of a set of planned, coordinated, and unified leadership, it will inevitably affect the government’s response speed and adaptability, and it will not be able to implement effective management, as shown in Figure1 [16]. Therefore, it is required to establish a chain of command that enables all participants in the emergency management work to work together, called an integrated emergency management system. Emergency management is a dynamic process that includes disaster mitigation, preparedness, response, and recovery. Disaster mitigation includes two meanings: Through preliminary work, we avoid avoidable disasters as much as possible and reduce the impact of unavoidable disasters as much as possible. In China, it is also called disaster reduction and prevention. Disaster mitigation measures cannot prevent disasters from occurring nor can they completely eliminate the vulnerability of a community or area’s facilities to all hazards. Therefore, it is necessary to be fully prepared for all kinds of dangers that may occur. The purpose of preparation is to ensure the emergency response capability required for emergency rescue of major accidents, mainly focusing on the development of emergency operation plans and systems. The main contents of preparation for extremes are preparation of plans, the establishment of early warning systems, emergency training, and emergency drills. Response is “all actions to save lives and reduce losses in an incident”. Recovery is after the disaster event is over, the return of disaster-stricken communities and people to normal life and production order before the disaster.Figure 1
Emergency management.


#### 3.1.2. The Importance of Information Integration in the Modern Emergency Management Theory

In accordance with the principles of “comprehensive coordination, professional disposal, territorial focus, and high authorization,” we scientifically define the relationship between the three levels of macrolevel strategic decision-making, mesolevel campaign command, and microlevel tactical action. However, grasping all kinds of information for the first time is the premise of professional command. In the past, most of the information was obtained by manual submission. Basically, front-line personnel collect information manually and report it layer by layer. This is not inefficient and it costs a lot of manpower. In the era of big data, the way of information collection has changed from manual collection to information collection through scientific and technological means. Countries around the world have gradually changed the traditional “human sea tactics” characterized by huge numbers and huge consumption; instead, by optimizing and integrating various scientific and technological resources, strengthening the research and development of key technologies such as monitoring and early warning, command, and dispatch, and equipment support, as well as the development of complete sets of equipment, accelerated the application of remote sensing, geographic information system, global positioning system, network communication technology, cloud computing, Internet of Things and other technologies, as well as the comprehensive integration and transformation of high-tech achievements, and improved the ability to respond to emergencies in the first time, on the spot and at the first place. For example, through the development of advanced earthquake early warning and tsunami monitoring and early warning systems, millions of people can receive early warning information several seconds before the arrival of a strong earthquake and shear waves and thousands of minutes before the arrival of a tsunami, providing opportunities for self-rescue escape and refuge. In particular, the advanced subway early warning and automatic shutdown system enabled 27 subway trains operating in the disaster area to stop safely, effectively preventing the occurrence of secondary disasters. Therefore, in emergency management, the premise for scientific decision-making is to quickly, accurately, and comprehensively collect information and present it to decision-makers [17].


#### 3.1.3. Changes in Information Integration Work in the Era of Big Data Technology

Data are considered to be the basic means of life and market elements in the new era as important as material assets and human capital. The explosion of information has led to the explosion of the amount of information, and the data accumulated from the beginning of human history to the 1980s are not as good as our current data; the amount of data we generate is very huge, and now, there is a new trend in the era of the Internet of things. In the era of the Internet of things, we often see automatically formed interactions and automatically formed data processing; then, we will target ten times, hundred times, thousand times the equipment or the data generated all the time, this is the challenge of our data, in such a large amount of data, how much value can be really mined from it is actually very limited.The explosive growth of information resources, among which the unstructured data information reaches about 85%, traditional information resource management technology has been unable to cope with the challenges of the big data era [18]. The emergence of big data technology and other big data tools and equipment, as well as the widespread use of cloud computing data processing and application models, provide an efficient, scalable, and low-cost solution for emergency management to deal with the growing mass of unstructured data, it makes up for the shortcomings of traditional relational databases or data warehouses in processing unstructured data, deepens and expands the intelligence and knowledge service capabilities, forms a data-driven decision-making mechanism, and improves the level of decision making.


### 3.2. Overview of Big Data Integration Technology

In the local government’s emergency management information integration work, the information and digital big data environment constitute its external macro environment. The government’s internal integration technical means and information communication channels constitute its internal microenvironment; the two together constitute the local government’s emergency management information integration environment.


#### 3.2.1. Data Collection

In the era of big data, government information resources are all-encompassing; on the one hand, a large amount of data are generated when interacting with external customers and partners through text information, social networks, mobile applications, etc.. On the other hand, a large amount of information is generated by daily administrative management activities such as internal production, office work, and video surveillance of the government. These information resources are represented in the form of text, images, audio, video, etc., and are a mixture of multimedia, multilanguage, and multitype information. We determine which data sources to select as analysis targets based on project planning and mission objectives, as well as data analysis needs. These data include database design specification, E-R diagram, outline design, system requirement analysis report, and system operation report. The more complete the data collection, the better the understanding of the data and the accuracy of subsequent data integration operations.


#### 3.2.2. Data Collation

The collected data may come from inside or outside the enterprise, and the platforms and formats of data sources are not necessarily the same. Different collection and processing methods are required for different data sources. The structure is complex and diverse and it is difficult to unify standards. In the era of big data, the organization of information resources is nonlinear, and hypertext and hypermedia information has gradually become the main way. Information resources on the same server may also differ in data structures, character sets, and processing methods. The complex and diverse structure of big data brings trouble to the establishment of unified standards and norms for information resources and makes the huge amount of structured and unstructured information resources in a disordered state. Standardization and standardization of enterprise information resources are one of the keys and difficult points of future enterprise informatization construction.


#### 3.2.3. Data Analysis

Research shows that the amount of digital information captured and generated in China is expected to increase to 8.5 ZB between 2015 and 2020, achieving a 22-fold growth, or maintaining a compound annual growth rate of 50% [19]. Finding relevant information in petabytes or even exabytes of data is tantamount to looking for a needle in a haystack, and the cost and complexity of using the information to drive decision making is increasing day by day.Generally, people who do data integration systems are not those who used to do operational databases for enterprises. Besides, there are many database systems in enterprises, which are generally completed by different personnel; therefore, it is very difficult to analyze data sources according to the found data, but this is an insurmountable work process and directly affects the quality of the new system. A very fundamental purpose of big data is to have very large storage and very large computing power, which can help us scale out the technologies we need to do.


#### 3.2.4. Data Conversion

The process of data conversion is actually the process of data mapping. If the previous steps of data source analysis are done well, then this step is relatively easy. It can be mapped at the analysis topic level, data source entity level, and attribute level.


### 3.3. Investigation of the Existing Emergency Management Information Integration Model in a City

Splitting and combining ordered information applies a hierarchy pattern. The mode of emergency information application of a city government is a split-type if-type hierarchical system, which is innovative from a single traditional distributed mode and a centralized mode, which meets the information integration needs of a city’s emergency linkage management. In this hierarchical structure model, there is a centralized and closed unified scheduler, which centralizes all the emergency information resources in the whole region and then hands them over to the main program, while the regional management information resources and organizational coordination information are passed through another independent is done by the scheduler, it supports the owners of remote information resources to implement specific individual preference schemes for specific external needs; at the same time, it is compatible with the independent maintenance functions of each subsystem; the central system only performs comprehensive overall scheduling for these subsystems, and matters within them retain their own management control. Obviously, a city’s split and combined hierarchical information processing structure system has well absorbed the advantages of a single centralized unified scheduling and a single distributed independent processing, so the integration of emergency linkage management information is more hierarchical [20] as shown in Figures 2(a)–2(c):Figure 2
Information integration management mode diagram. (a) Centralized management model. (b) Distributed management model. (c) Hierarchical management model.
(a)(b)(c)In the process of local government emergency information integration, the main body of integration should extract the commonalities and individual characteristics in the information resource integration channels according to the current supply and demand of local actual information, human resources, and other resources, using the split-combined hierarchical model to interconnect the different information integration channels, form an abstract model of emergency management information integration channels, and establish a concrete model according to the government affairs process, that is, the coexistence of multiple integration modes of component order integration, conditional selection integration, repeated integration, and parallel integration. The emergency information management platform of a city has constructed four routing relationships of parallel, condition, repetition, and sequence in accordance with the logical rules of the business processes of each department, so that the entire emergency information integration process has been interconnected, and significant results have been achieved in both the information update cycle and the information communication function. We form an ontology-based global mechanism. Before the establishment of the emergency linkage management office, various government organizations in a certain city used different information reporting and issuing methods to transmit the same information; due to too many transmission channels, it is easy to cause misinterpretation and low accuracy of the information in the process of information transmission; in the end, multiple versions of the same event information appeared, which undoubtedly had a huge negative impact on the feasibility and integrity of the information; in response to this thorny problem, the information management department of a city government, together with the public security, fire protection, and medical units, conducted an information communication reform attempts. All crisis cases, disposal information, etc., are incorporated into the government’s unified split-level business flow model, and the goal of mapping and converting heterogeneous data sources to the global model has been preliminarily achieved. Based on the global mechanism of ontology, enhanced information integration, and sharing among departments across the region, the operation process of the emergency linkage center is shown in Figure3.Figure 3
Operation process of emergency linkage center.It is obviously reasonable to look at the measures of a city government from a technical point of view, because even if the government manages the flow of information resources in emergency response [21]. Data sharing will involve organizations, departments, and information platforms with different permissions. However, after compatible processing through big data network technology, it has become a reality to transform the real “heterogeneous” environment into a virtual “homogeneous” environment, it can combine the same emergency management information with different description semantics; after the global integration mechanism based on the same ontology is transformed into the integration problem of different modes, the information is finally transmitted accurately, and the effective optimization and integration of various information resources are finally realized for scientific scheduling and management.


## 3.1. Overview of Government Emergency Management Theory and Practice

### 3.1.1. Basic Theory of Emergency Management

Integrated emergency management system is a term commonly used in public safety management, or “Emergency Management Partnership” or called “All Agency Approach/All-agencies Approach” or “Integrated Approach”. When emergencies occur, representatives from different agencies, departments, and all levels of government are required to work together and cooperate with each other and decisions must be made quickly. If there is a lack of a set of planned, coordinated, and unified leadership, it will inevitably affect the government’s response speed and adaptability, and it will not be able to implement effective management, as shown in Figure1 [16]. Therefore, it is required to establish a chain of command that enables all participants in the emergency management work to work together, called an integrated emergency management system. Emergency management is a dynamic process that includes disaster mitigation, preparedness, response, and recovery. Disaster mitigation includes two meanings: Through preliminary work, we avoid avoidable disasters as much as possible and reduce the impact of unavoidable disasters as much as possible. In China, it is also called disaster reduction and prevention. Disaster mitigation measures cannot prevent disasters from occurring nor can they completely eliminate the vulnerability of a community or area’s facilities to all hazards. Therefore, it is necessary to be fully prepared for all kinds of dangers that may occur. The purpose of preparation is to ensure the emergency response capability required for emergency rescue of major accidents, mainly focusing on the development of emergency operation plans and systems. The main contents of preparation for extremes are preparation of plans, the establishment of early warning systems, emergency training, and emergency drills. Response is “all actions to save lives and reduce losses in an incident”. Recovery is after the disaster event is over, the return of disaster-stricken communities and people to normal life and production order before the disaster.Figure 1
Emergency management.


### 3.1.2. The Importance of Information Integration in the Modern Emergency Management Theory

In accordance with the principles of “comprehensive coordination, professional disposal, territorial focus, and high authorization,” we scientifically define the relationship between the three levels of macrolevel strategic decision-making, mesolevel campaign command, and microlevel tactical action. However, grasping all kinds of information for the first time is the premise of professional command. In the past, most of the information was obtained by manual submission. Basically, front-line personnel collect information manually and report it layer by layer. This is not inefficient and it costs a lot of manpower. In the era of big data, the way of information collection has changed from manual collection to information collection through scientific and technological means. Countries around the world have gradually changed the traditional “human sea tactics” characterized by huge numbers and huge consumption; instead, by optimizing and integrating various scientific and technological resources, strengthening the research and development of key technologies such as monitoring and early warning, command, and dispatch, and equipment support, as well as the development of complete sets of equipment, accelerated the application of remote sensing, geographic information system, global positioning system, network communication technology, cloud computing, Internet of Things and other technologies, as well as the comprehensive integration and transformation of high-tech achievements, and improved the ability to respond to emergencies in the first time, on the spot and at the first place. For example, through the development of advanced earthquake early warning and tsunami monitoring and early warning systems, millions of people can receive early warning information several seconds before the arrival of a strong earthquake and shear waves and thousands of minutes before the arrival of a tsunami, providing opportunities for self-rescue escape and refuge. In particular, the advanced subway early warning and automatic shutdown system enabled 27 subway trains operating in the disaster area to stop safely, effectively preventing the occurrence of secondary disasters. Therefore, in emergency management, the premise for scientific decision-making is to quickly, accurately, and comprehensively collect information and present it to decision-makers [17].


### 3.1.3. Changes in Information Integration Work in the Era of Big Data Technology

Data are considered to be the basic means of life and market elements in the new era as important as material assets and human capital. The explosion of information has led to the explosion of the amount of information, and the data accumulated from the beginning of human history to the 1980s are not as good as our current data; the amount of data we generate is very huge, and now, there is a new trend in the era of the Internet of things. In the era of the Internet of things, we often see automatically formed interactions and automatically formed data processing; then, we will target ten times, hundred times, thousand times the equipment or the data generated all the time, this is the challenge of our data, in such a large amount of data, how much value can be really mined from it is actually very limited.The explosive growth of information resources, among which the unstructured data information reaches about 85%, traditional information resource management technology has been unable to cope with the challenges of the big data era [18]. The emergence of big data technology and other big data tools and equipment, as well as the widespread use of cloud computing data processing and application models, provide an efficient, scalable, and low-cost solution for emergency management to deal with the growing mass of unstructured data, it makes up for the shortcomings of traditional relational databases or data warehouses in processing unstructured data, deepens and expands the intelligence and knowledge service capabilities, forms a data-driven decision-making mechanism, and improves the level of decision making.


## 3.1.1. Basic Theory of Emergency Management

Integrated emergency management system is a term commonly used in public safety management, or “Emergency Management Partnership” or called “All Agency Approach/All-agencies Approach” or “Integrated Approach”. When emergencies occur, representatives from different agencies, departments, and all levels of government are required to work together and cooperate with each other and decisions must be made quickly. If there is a lack of a set of planned, coordinated, and unified leadership, it will inevitably affect the government’s response speed and adaptability, and it will not be able to implement effective management, as shown in Figure1 [16]. Therefore, it is required to establish a chain of command that enables all participants in the emergency management work to work together, called an integrated emergency management system. Emergency management is a dynamic process that includes disaster mitigation, preparedness, response, and recovery. Disaster mitigation includes two meanings: Through preliminary work, we avoid avoidable disasters as much as possible and reduce the impact of unavoidable disasters as much as possible. In China, it is also called disaster reduction and prevention. Disaster mitigation measures cannot prevent disasters from occurring nor can they completely eliminate the vulnerability of a community or area’s facilities to all hazards. Therefore, it is necessary to be fully prepared for all kinds of dangers that may occur. The purpose of preparation is to ensure the emergency response capability required for emergency rescue of major accidents, mainly focusing on the development of emergency operation plans and systems. The main contents of preparation for extremes are preparation of plans, the establishment of early warning systems, emergency training, and emergency drills. Response is “all actions to save lives and reduce losses in an incident”. Recovery is after the disaster event is over, the return of disaster-stricken communities and people to normal life and production order before the disaster.Figure 1
Emergency management.


## 3.1.2. The Importance of Information Integration in the Modern Emergency Management Theory

In accordance with the principles of “comprehensive coordination, professional disposal, territorial focus, and high authorization,” we scientifically define the relationship between the three levels of macrolevel strategic decision-making, mesolevel campaign command, and microlevel tactical action. However, grasping all kinds of information for the first time is the premise of professional command. In the past, most of the information was obtained by manual submission. Basically, front-line personnel collect information manually and report it layer by layer. This is not inefficient and it costs a lot of manpower. In the era of big data, the way of information collection has changed from manual collection to information collection through scientific and technological means. Countries around the world have gradually changed the traditional “human sea tactics” characterized by huge numbers and huge consumption; instead, by optimizing and integrating various scientific and technological resources, strengthening the research and development of key technologies such as monitoring and early warning, command, and dispatch, and equipment support, as well as the development of complete sets of equipment, accelerated the application of remote sensing, geographic information system, global positioning system, network communication technology, cloud computing, Internet of Things and other technologies, as well as the comprehensive integration and transformation of high-tech achievements, and improved the ability to respond to emergencies in the first time, on the spot and at the first place. For example, through the development of advanced earthquake early warning and tsunami monitoring and early warning systems, millions of people can receive early warning information several seconds before the arrival of a strong earthquake and shear waves and thousands of minutes before the arrival of a tsunami, providing opportunities for self-rescue escape and refuge. In particular, the advanced subway early warning and automatic shutdown system enabled 27 subway trains operating in the disaster area to stop safely, effectively preventing the occurrence of secondary disasters. Therefore, in emergency management, the premise for scientific decision-making is to quickly, accurately, and comprehensively collect information and present it to decision-makers [17].


## 3.1.3. Changes in Information Integration Work in the Era of Big Data Technology

Data are considered to be the basic means of life and market elements in the new era as important as material assets and human capital. The explosion of information has led to the explosion of the amount of information, and the data accumulated from the beginning of human history to the 1980s are not as good as our current data; the amount of data we generate is very huge, and now, there is a new trend in the era of the Internet of things. In the era of the Internet of things, we often see automatically formed interactions and automatically formed data processing; then, we will target ten times, hundred times, thousand times the equipment or the data generated all the time, this is the challenge of our data, in such a large amount of data, how much value can be really mined from it is actually very limited.The explosive growth of information resources, among which the unstructured data information reaches about 85%, traditional information resource management technology has been unable to cope with the challenges of the big data era [18]. The emergence of big data technology and other big data tools and equipment, as well as the widespread use of cloud computing data processing and application models, provide an efficient, scalable, and low-cost solution for emergency management to deal with the growing mass of unstructured data, it makes up for the shortcomings of traditional relational databases or data warehouses in processing unstructured data, deepens and expands the intelligence and knowledge service capabilities, forms a data-driven decision-making mechanism, and improves the level of decision making.


## 3.2. Overview of Big Data Integration Technology

In the local government’s emergency management information integration work, the information and digital big data environment constitute its external macro environment. The government’s internal integration technical means and information communication channels constitute its internal microenvironment; the two together constitute the local government’s emergency management information integration environment.


### 3.2.1. Data Collection

In the era of big data, government information resources are all-encompassing; on the one hand, a large amount of data are generated when interacting with external customers and partners through text information, social networks, mobile applications, etc.. On the other hand, a large amount of information is generated by daily administrative management activities such as internal production, office work, and video surveillance of the government. These information resources are represented in the form of text, images, audio, video, etc., and are a mixture of multimedia, multilanguage, and multitype information. We determine which data sources to select as analysis targets based on project planning and mission objectives, as well as data analysis needs. These data include database design specification, E-R diagram, outline design, system requirement analysis report, and system operation report. The more complete the data collection, the better the understanding of the data and the accuracy of subsequent data integration operations.


### 3.2.2. Data Collation

The collected data may come from inside or outside the enterprise, and the platforms and formats of data sources are not necessarily the same. Different collection and processing methods are required for different data sources. The structure is complex and diverse and it is difficult to unify standards. In the era of big data, the organization of information resources is nonlinear, and hypertext and hypermedia information has gradually become the main way. Information resources on the same server may also differ in data structures, character sets, and processing methods. The complex and diverse structure of big data brings trouble to the establishment of unified standards and norms for information resources and makes the huge amount of structured and unstructured information resources in a disordered state. Standardization and standardization of enterprise information resources are one of the keys and difficult points of future enterprise informatization construction.


### 3.2.3. Data Analysis

Research shows that the amount of digital information captured and generated in China is expected to increase to 8.5 ZB between 2015 and 2020, achieving a 22-fold growth, or maintaining a compound annual growth rate of 50% [19]. Finding relevant information in petabytes or even exabytes of data is tantamount to looking for a needle in a haystack, and the cost and complexity of using the information to drive decision making is increasing day by day.Generally, people who do data integration systems are not those who used to do operational databases for enterprises. Besides, there are many database systems in enterprises, which are generally completed by different personnel; therefore, it is very difficult to analyze data sources according to the found data, but this is an insurmountable work process and directly affects the quality of the new system. A very fundamental purpose of big data is to have very large storage and very large computing power, which can help us scale out the technologies we need to do.


### 3.2.4. Data Conversion

The process of data conversion is actually the process of data mapping. If the previous steps of data source analysis are done well, then this step is relatively easy. It can be mapped at the analysis topic level, data source entity level, and attribute level.


## 3.2.1. Data Collection

In the era of big data, government information resources are all-encompassing; on the one hand, a large amount of data are generated when interacting with external customers and partners through text information, social networks, mobile applications, etc.. On the other hand, a large amount of information is generated by daily administrative management activities such as internal production, office work, and video surveillance of the government. These information resources are represented in the form of text, images, audio, video, etc., and are a mixture of multimedia, multilanguage, and multitype information. We determine which data sources to select as analysis targets based on project planning and mission objectives, as well as data analysis needs. These data include database design specification, E-R diagram, outline design, system requirement analysis report, and system operation report. The more complete the data collection, the better the understanding of the data and the accuracy of subsequent data integration operations.


## 3.2.2. Data Collation

The collected data may come from inside or outside the enterprise, and the platforms and formats of data sources are not necessarily the same. Different collection and processing methods are required for different data sources. The structure is complex and diverse and it is difficult to unify standards. In the era of big data, the organization of information resources is nonlinear, and hypertext and hypermedia information has gradually become the main way. Information resources on the same server may also differ in data structures, character sets, and processing methods. The complex and diverse structure of big data brings trouble to the establishment of unified standards and norms for information resources and makes the huge amount of structured and unstructured information resources in a disordered state. Standardization and standardization of enterprise information resources are one of the keys and difficult points of future enterprise informatization construction.


## 3.2.3. Data Analysis

Research shows that the amount of digital information captured and generated in China is expected to increase to 8.5 ZB between 2015 and 2020, achieving a 22-fold growth, or maintaining a compound annual growth rate of 50% [19]. Finding relevant information in petabytes or even exabytes of data is tantamount to looking for a needle in a haystack, and the cost and complexity of using the information to drive decision making is increasing day by day.Generally, people who do data integration systems are not those who used to do operational databases for enterprises. Besides, there are many database systems in enterprises, which are generally completed by different personnel; therefore, it is very difficult to analyze data sources according to the found data, but this is an insurmountable work process and directly affects the quality of the new system. A very fundamental purpose of big data is to have very large storage and very large computing power, which can help us scale out the technologies we need to do.


## 3.2.4. Data Conversion

The process of data conversion is actually the process of data mapping. If the previous steps of data source analysis are done well, then this step is relatively easy. It can be mapped at the analysis topic level, data source entity level, and attribute level.


## 3.3. Investigation of the Existing Emergency Management Information Integration Model in a City

Splitting and combining ordered information applies a hierarchy pattern. The mode of emergency information application of a city government is a split-type if-type hierarchical system, which is innovative from a single traditional distributed mode and a centralized mode, which meets the information integration needs of a city’s emergency linkage management. In this hierarchical structure model, there is a centralized and closed unified scheduler, which centralizes all the emergency information resources in the whole region and then hands them over to the main program, while the regional management information resources and organizational coordination information are passed through another independent is done by the scheduler, it supports the owners of remote information resources to implement specific individual preference schemes for specific external needs; at the same time, it is compatible with the independent maintenance functions of each subsystem; the central system only performs comprehensive overall scheduling for these subsystems, and matters within them retain their own management control. Obviously, a city’s split and combined hierarchical information processing structure system has well absorbed the advantages of a single centralized unified scheduling and a single distributed independent processing, so the integration of emergency linkage management information is more hierarchical [20] as shown in Figures 2(a)–2(c):Figure 2
Information integration management mode diagram. (a) Centralized management model. (b) Distributed management model. (c) Hierarchical management model.
(a)(b)(c)In the process of local government emergency information integration, the main body of integration should extract the commonalities and individual characteristics in the information resource integration channels according to the current supply and demand of local actual information, human resources, and other resources, using the split-combined hierarchical model to interconnect the different information integration channels, form an abstract model of emergency management information integration channels, and establish a concrete model according to the government affairs process, that is, the coexistence of multiple integration modes of component order integration, conditional selection integration, repeated integration, and parallel integration. The emergency information management platform of a city has constructed four routing relationships of parallel, condition, repetition, and sequence in accordance with the logical rules of the business processes of each department, so that the entire emergency information integration process has been interconnected, and significant results have been achieved in both the information update cycle and the information communication function. We form an ontology-based global mechanism. Before the establishment of the emergency linkage management office, various government organizations in a certain city used different information reporting and issuing methods to transmit the same information; due to too many transmission channels, it is easy to cause misinterpretation and low accuracy of the information in the process of information transmission; in the end, multiple versions of the same event information appeared, which undoubtedly had a huge negative impact on the feasibility and integrity of the information; in response to this thorny problem, the information management department of a city government, together with the public security, fire protection, and medical units, conducted an information communication reform attempts. All crisis cases, disposal information, etc., are incorporated into the government’s unified split-level business flow model, and the goal of mapping and converting heterogeneous data sources to the global model has been preliminarily achieved. Based on the global mechanism of ontology, enhanced information integration, and sharing among departments across the region, the operation process of the emergency linkage center is shown in Figure3.Figure 3
Operation process of emergency linkage center.It is obviously reasonable to look at the measures of a city government from a technical point of view, because even if the government manages the flow of information resources in emergency response [21]. Data sharing will involve organizations, departments, and information platforms with different permissions. However, after compatible processing through big data network technology, it has become a reality to transform the real “heterogeneous” environment into a virtual “homogeneous” environment, it can combine the same emergency management information with different description semantics; after the global integration mechanism based on the same ontology is transformed into the integration problem of different modes, the information is finally transmitted accurately, and the effective optimization and integration of various information resources are finally realized for scientific scheduling and management.


## 4. Analysis of Results

### 4.1. Survey Objects and Process

This survey uses the questionnaire method and interview method to conduct field investigations on some government agencies in a city. The general object of the investigation is the current situation of emergency linkage information integration of a municipal government. A total of 350 questionnaires were distributed, 335 valid questionnaires were recovered, and the questionnaire recovery rate was 95.7%. Among them, 300 self-administered questionnaires were distributed to the staff of functional organizations; 50 interview questionnaires were distributed to leading cadres. The processing of the questionnaire data adopts Visual FoxPro, Excel, and other software for statistical verification.The basic idea of the paired samplet test is to set the population X1 to obey the normal distribution Nμ1,σ12, and the population to obey the normal distribution Nμ2,σ22, samples x11,x12,…,x1n, and x21,x22,…,x2n are drawn from these two populations, respectively, and the two samples are paired with each other. It is required to test whether μ1 and μ2 are significantly different. Specific steps are as follows:(1)
Introduce variablesIntroduce a new random variableY=X1−X2, the corresponding sample value is y1,y2,…,yn, where yi=x1i−x2ii=1,2,…,n.(2)
Establish the assumption as follows (1)(1)H0:μY=0.(3)
Calculation formula and meaning(2)t=y¯sy/n,wherey¯=∑i=1nyi/n is the mean of the paired sample differences; Sy=∑i=1nyi−y¯2/n−1 is the standard deviation of the paired sample differences; and n is the number of paired samples.This statistict follows a t-distribution with n−1 degrees of freedom under the condition that the null hypothesis (μY=0) is true.


### 4.2. Questionnaire Design and Distribution

This questionnaire consists of 25 closed-ended questions and 5 semi-open-ended questions; the main contents include survey on the information communication platform of government departments, a survey on information sharing willingness of various departments and staff, a survey on the overall level of information sharing in a city including public security, finance, human resources, and education systems, and a survey on the influencing factors of information sharing by government functional departments.


### 4.3. Questionnaire Survey Results

#### 4.3.1. Lack of the Information Integration Platform

Compared with the information sharing platforms owned by the administrative systems of the more developed cities in China (as shown in Table1 and Figure 4), it can be seen that the number of information sharing platforms in the administrative system of a city is very lacking and can only basically meet the requirements of its jurisdiction. Information sharing needs. The data comparison shows that the public security system with the most information sharing platforms in a city differs by 21 units from the public security system in developed cities. The number of information sharing platforms for information management systems in a city is 30, while that in developed cities is 78, a difference of 48 units. The education system has the least number of platforms in a city’s administrative system, with only 9 platforms, the administrative system with the least number of platforms in a developed city is the civil affairs system, with 37 platforms, 28 more than a city. These numerical gaps basically reflect the gap between a city’s information sharing hardware and other developed regions in China.Table 1
Number of government information management platforms in some developed cities.
Department nameNumber of emergency management platforms (unit: units)Network equipmentDegree of information sharingPublic security system63High qualityGeneralFinancial system43High qualityHighCivil affairs system37GenerallyHighEducation system38High qualityHighInformation management system78PremiumHighFigure 4
The number of some government information management platforms in a city.


#### 4.3.2. Not Willing to Share Information

Regarding the disclosure and sharing of daily common information of government departments, more than 50% of units or individuals believe that cross-departmental information sharing is necessary and feasible; However, when it comes to the core interests of the department, such as the property of officials and the specific procedures of the disaster relief plan, the vast majority of departments are still opposed.It shows that despite the background of big data, there are still many departments in the consideration of departmental interests, and reluctance to provide the department’s data. In fact, the data are not only the appearance of information gaps between departments but also reveal some hidden reasons behind the reluctance of various departments to share their own departments with other departments. Based on their own short-term interests, many departments usually treat information sharing in a conservative manner and are unwilling to share their own information and data, which directly leads to the fragmentation and isolation of emergency management information. There are also department leaders or managers who have a relatively shallow understanding of the application of big data technology and are overly worried about the risk of leakage of departmental confidential information caused by information sharing. The deep-seated reason why some departments are reluctant to share information across departments is that the business of this department is completely different from that of other departments, and its powers and responsibilities are irrelevant; therefore, there is a bystander attitude of “everyone sweeps the snow in front of the door, and does not care about the frost on other people’s tiles”. In addition, based on privacy protection considerations, many government departments are reluctant to take the risk of information leakage due to information sharing and would rather sacrifice convenience than share information [22]. Therefore, in actual operation, the level of information sharing between departments is extremely low; it can be said that the information communication channels between horizontal government departments are not smooth.


#### 4.3.3. The Reasons That Affect the Integration of Emergency Linkage Information Are Complex

According to the survey results of “the reasons that affect the integration of emergency linkage information of a city government” (see Figure5), the first is the poor information communication channels between departments, accounting for 22.7%. The second and third are “administrative system restrictions” and “protection of the interests of the department,” accounting for 21.4% and 19.4% respectively. It is worth noting that the technical problem of information management is also one of the important factors affecting the government’s emergency response management, accounting for 19.1%. Obviously, the factors affecting the integration of emergency linkage information of a city government are both objective and subjective, both internal and external. It can be said that the influencing factors are complicated and summed up as follows: China’s current government organizations are slightly bloated, with too many management levels and confusing powers and responsibilities, which will inevitably increase the number of information transmission links, which is quite unfavorable for the dissemination of work information; otherwise, the accuracy of many critical emergency information will be affected to varying degrees, which will inevitably affect the management of emergency linkage information and the progress of crisis disposal. There are information gaps between various departments and lack of crisis management mechanism, as a result, the existing emergency linkage management information system faces greater difficulties and challenges, and the theoretical collaborative combat effectiveness has not been fully reflected in practical operations. Furthermore, the top-down one-way one-line communication method is too simple, if all emergency linkage information is top-down one-line communication, the speed of information dissemination will be slow and the feedback information will be less. In addition, in the reporting of crisis accident information, in order to maintain the performance and interests of the department, local government departments usually report lightly or delay reporting, resulting in the dilemma of unbalanced emergency information. Under the management system of the existing traditional government departments, various units and departments of local governments still have difficulties such as lack of unity, information occlusion, and poor management communication and coordination in the public crisis, after forming a pattern of police and civilians, participation in multiple subjects, and multisector linkage; however, in terms of actual operation, it is far from exerting emergency linkage management.Figure 5
A survey of the reasons that affect the integration of emergency linkage information in a municipal government.


## 4.1. Survey Objects and Process

This survey uses the questionnaire method and interview method to conduct field investigations on some government agencies in a city. The general object of the investigation is the current situation of emergency linkage information integration of a municipal government. A total of 350 questionnaires were distributed, 335 valid questionnaires were recovered, and the questionnaire recovery rate was 95.7%. Among them, 300 self-administered questionnaires were distributed to the staff of functional organizations; 50 interview questionnaires were distributed to leading cadres. The processing of the questionnaire data adopts Visual FoxPro, Excel, and other software for statistical verification.The basic idea of the paired samplet test is to set the population X1 to obey the normal distribution Nμ1,σ12, and the population to obey the normal distribution Nμ2,σ22, samples x11,x12,…,x1n, and x21,x22,…,x2n are drawn from these two populations, respectively, and the two samples are paired with each other. It is required to test whether μ1 and μ2 are significantly different. Specific steps are as follows:(1)
Introduce variablesIntroduce a new random variableY=X1−X2, the corresponding sample value is y1,y2,…,yn, where yi=x1i−x2ii=1,2,…,n.(2)
Establish the assumption as follows (1)(1)H0:μY=0.(3)
Calculation formula and meaning(2)t=y¯sy/n,wherey¯=∑i=1nyi/n is the mean of the paired sample differences; Sy=∑i=1nyi−y¯2/n−1 is the standard deviation of the paired sample differences; and n is the number of paired samples.This statistict follows a t-distribution with n−1 degrees of freedom under the condition that the null hypothesis (μY=0) is true.


## 4.2. Questionnaire Design and Distribution

This questionnaire consists of 25 closed-ended questions and 5 semi-open-ended questions; the main contents include survey on the information communication platform of government departments, a survey on information sharing willingness of various departments and staff, a survey on the overall level of information sharing in a city including public security, finance, human resources, and education systems, and a survey on the influencing factors of information sharing by government functional departments.


## 4.3. Questionnaire Survey Results

### 4.3.1. Lack of the Information Integration Platform

Compared with the information sharing platforms owned by the administrative systems of the more developed cities in China (as shown in Table1 and Figure 4), it can be seen that the number of information sharing platforms in the administrative system of a city is very lacking and can only basically meet the requirements of its jurisdiction. Information sharing needs. The data comparison shows that the public security system with the most information sharing platforms in a city differs by 21 units from the public security system in developed cities. The number of information sharing platforms for information management systems in a city is 30, while that in developed cities is 78, a difference of 48 units. The education system has the least number of platforms in a city’s administrative system, with only 9 platforms, the administrative system with the least number of platforms in a developed city is the civil affairs system, with 37 platforms, 28 more than a city. These numerical gaps basically reflect the gap between a city’s information sharing hardware and other developed regions in China.Table 1
Number of government information management platforms in some developed cities.
Department nameNumber of emergency management platforms (unit: units)Network equipmentDegree of information sharingPublic security system63High qualityGeneralFinancial system43High qualityHighCivil affairs system37GenerallyHighEducation system38High qualityHighInformation management system78PremiumHighFigure 4
The number of some government information management platforms in a city.


### 4.3.2. Not Willing to Share Information

Regarding the disclosure and sharing of daily common information of government departments, more than 50% of units or individuals believe that cross-departmental information sharing is necessary and feasible; However, when it comes to the core interests of the department, such as the property of officials and the specific procedures of the disaster relief plan, the vast majority of departments are still opposed.It shows that despite the background of big data, there are still many departments in the consideration of departmental interests, and reluctance to provide the department’s data. In fact, the data are not only the appearance of information gaps between departments but also reveal some hidden reasons behind the reluctance of various departments to share their own departments with other departments. Based on their own short-term interests, many departments usually treat information sharing in a conservative manner and are unwilling to share their own information and data, which directly leads to the fragmentation and isolation of emergency management information. There are also department leaders or managers who have a relatively shallow understanding of the application of big data technology and are overly worried about the risk of leakage of departmental confidential information caused by information sharing. The deep-seated reason why some departments are reluctant to share information across departments is that the business of this department is completely different from that of other departments, and its powers and responsibilities are irrelevant; therefore, there is a bystander attitude of “everyone sweeps the snow in front of the door, and does not care about the frost on other people’s tiles”. In addition, based on privacy protection considerations, many government departments are reluctant to take the risk of information leakage due to information sharing and would rather sacrifice convenience than share information [22]. Therefore, in actual operation, the level of information sharing between departments is extremely low; it can be said that the information communication channels between horizontal government departments are not smooth.


### 4.3.3. The Reasons That Affect the Integration of Emergency Linkage Information Are Complex

According to the survey results of “the reasons that affect the integration of emergency linkage information of a city government” (see Figure5), the first is the poor information communication channels between departments, accounting for 22.7%. The second and third are “administrative system restrictions” and “protection of the interests of the department,” accounting for 21.4% and 19.4% respectively. It is worth noting that the technical problem of information management is also one of the important factors affecting the government’s emergency response management, accounting for 19.1%. Obviously, the factors affecting the integration of emergency linkage information of a city government are both objective and subjective, both internal and external. It can be said that the influencing factors are complicated and summed up as follows: China’s current government organizations are slightly bloated, with too many management levels and confusing powers and responsibilities, which will inevitably increase the number of information transmission links, which is quite unfavorable for the dissemination of work information; otherwise, the accuracy of many critical emergency information will be affected to varying degrees, which will inevitably affect the management of emergency linkage information and the progress of crisis disposal. There are information gaps between various departments and lack of crisis management mechanism, as a result, the existing emergency linkage management information system faces greater difficulties and challenges, and the theoretical collaborative combat effectiveness has not been fully reflected in practical operations. Furthermore, the top-down one-way one-line communication method is too simple, if all emergency linkage information is top-down one-line communication, the speed of information dissemination will be slow and the feedback information will be less. In addition, in the reporting of crisis accident information, in order to maintain the performance and interests of the department, local government departments usually report lightly or delay reporting, resulting in the dilemma of unbalanced emergency information. Under the management system of the existing traditional government departments, various units and departments of local governments still have difficulties such as lack of unity, information occlusion, and poor management communication and coordination in the public crisis, after forming a pattern of police and civilians, participation in multiple subjects, and multisector linkage; however, in terms of actual operation, it is far from exerting emergency linkage management.Figure 5
A survey of the reasons that affect the integration of emergency linkage information in a municipal government.


## 4.3.1. Lack of the Information Integration Platform

Compared with the information sharing platforms owned by the administrative systems of the more developed cities in China (as shown in Table1 and Figure 4), it can be seen that the number of information sharing platforms in the administrative system of a city is very lacking and can only basically meet the requirements of its jurisdiction. Information sharing needs. The data comparison shows that the public security system with the most information sharing platforms in a city differs by 21 units from the public security system in developed cities. The number of information sharing platforms for information management systems in a city is 30, while that in developed cities is 78, a difference of 48 units. The education system has the least number of platforms in a city’s administrative system, with only 9 platforms, the administrative system with the least number of platforms in a developed city is the civil affairs system, with 37 platforms, 28 more than a city. These numerical gaps basically reflect the gap between a city’s information sharing hardware and other developed regions in China.Table 1
Number of government information management platforms in some developed cities.
Department nameNumber of emergency management platforms (unit: units)Network equipmentDegree of information sharingPublic security system63High qualityGeneralFinancial system43High qualityHighCivil affairs system37GenerallyHighEducation system38High qualityHighInformation management system78PremiumHighFigure 4
The number of some government information management platforms in a city.


## 4.3.2. Not Willing to Share Information

Regarding the disclosure and sharing of daily common information of government departments, more than 50% of units or individuals believe that cross-departmental information sharing is necessary and feasible; However, when it comes to the core interests of the department, such as the property of officials and the specific procedures of the disaster relief plan, the vast majority of departments are still opposed.It shows that despite the background of big data, there are still many departments in the consideration of departmental interests, and reluctance to provide the department’s data. In fact, the data are not only the appearance of information gaps between departments but also reveal some hidden reasons behind the reluctance of various departments to share their own departments with other departments. Based on their own short-term interests, many departments usually treat information sharing in a conservative manner and are unwilling to share their own information and data, which directly leads to the fragmentation and isolation of emergency management information. There are also department leaders or managers who have a relatively shallow understanding of the application of big data technology and are overly worried about the risk of leakage of departmental confidential information caused by information sharing. The deep-seated reason why some departments are reluctant to share information across departments is that the business of this department is completely different from that of other departments, and its powers and responsibilities are irrelevant; therefore, there is a bystander attitude of “everyone sweeps the snow in front of the door, and does not care about the frost on other people’s tiles”. In addition, based on privacy protection considerations, many government departments are reluctant to take the risk of information leakage due to information sharing and would rather sacrifice convenience than share information [22]. Therefore, in actual operation, the level of information sharing between departments is extremely low; it can be said that the information communication channels between horizontal government departments are not smooth.


## 4.3.3. The Reasons That Affect the Integration of Emergency Linkage Information Are Complex

According to the survey results of “the reasons that affect the integration of emergency linkage information of a city government” (see Figure5), the first is the poor information communication channels between departments, accounting for 22.7%. The second and third are “administrative system restrictions” and “protection of the interests of the department,” accounting for 21.4% and 19.4% respectively. It is worth noting that the technical problem of information management is also one of the important factors affecting the government’s emergency response management, accounting for 19.1%. Obviously, the factors affecting the integration of emergency linkage information of a city government are both objective and subjective, both internal and external. It can be said that the influencing factors are complicated and summed up as follows: China’s current government organizations are slightly bloated, with too many management levels and confusing powers and responsibilities, which will inevitably increase the number of information transmission links, which is quite unfavorable for the dissemination of work information; otherwise, the accuracy of many critical emergency information will be affected to varying degrees, which will inevitably affect the management of emergency linkage information and the progress of crisis disposal. There are information gaps between various departments and lack of crisis management mechanism, as a result, the existing emergency linkage management information system faces greater difficulties and challenges, and the theoretical collaborative combat effectiveness has not been fully reflected in practical operations. Furthermore, the top-down one-way one-line communication method is too simple, if all emergency linkage information is top-down one-line communication, the speed of information dissemination will be slow and the feedback information will be less. In addition, in the reporting of crisis accident information, in order to maintain the performance and interests of the department, local government departments usually report lightly or delay reporting, resulting in the dilemma of unbalanced emergency information. Under the management system of the existing traditional government departments, various units and departments of local governments still have difficulties such as lack of unity, information occlusion, and poor management communication and coordination in the public crisis, after forming a pattern of police and civilians, participation in multiple subjects, and multisector linkage; however, in terms of actual operation, it is far from exerting emergency linkage management.Figure 5
A survey of the reasons that affect the integration of emergency linkage information in a municipal government.


## 5. Conclusion

The use of information technology can promote the unified “big linkage” reform of information flow, workflow, and responsibility flow; there are still some problems in practice, especially in the field of social management difficulties with relatively lagging law and system construction, and cross-responsibilities; some line departments have the responsibility of drilling legal vulnerabilities and “inaction in accordance with the law,” which leads to “connect” in form, but it cannot be “moved” in the solution mechanism of the problem. Second, the integration of human resources is very difficult to be restricted by the interests of the department. We analyze the main disadvantages and reasons of existing sharing models. At the same time, in combination with the application methods of big data in other industries, we analyze the needs of data sharing in the field of emergency management, so as to build a reasonable information sharing work model.



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*Source: 6813463-2022-09-22.xml*