Discussion on the Construction of Public Security Data Management

Capability Maturity Model

Qianqian He and Lin Jiang

Chongqing Medical and Pharmaceutical College, Chongqing, China

Keywords: Public Security Data, Management Ability, Maturity Model, Construct Strategy.

Abstract: At present, in the research process of security data management capability maturity model, the research work

of data management process is mainly completed. At the same time, it is necessary to fully grasp the research

status and application of the public security data management capability maturity model, analyze the

characteristics of the maturity model, and construct the public security data management capability maturity

model according to the specific types of public security data. We can use the capability maturity model to

effectively evaluate various problems in the process of public security data management, which is of great

help to improve the public security data management capability.

1 INTRODUCTION

As a new interdisciplinary subject, public security

data management involves a lot of contents in the

research process. The main purpose is to explore the

specific needs of public security governance activities

in information space in physical space and social

space, and to analyze the laws and characteristics of

public security data. We should use the knowledge of

data science and public security to fuse the data

problems in public security governance activities, pay

attention to the management of public security data

itself, and dig deep into the application value of data

in public security governance. Effective data

management generally requires long-term

management planning, and at the same time, it is

necessary to use corresponding management

activities at appropriate nodes to carry out

collaboration among personnel, institutions,

resources and key events. In this management

process, the data management model is an important

bridge connecting management strategy and

management practice, and plays a fundamental role.

Based on the related research contents in the field of

scientific data management and government data

management, the related models of data management

have been put forward, and the data management

infrastructure model and data management capability

maturity model have been formed. These typical

models can play a visual role in the application

process, clarify the complex process of data

management, and decompose the data management

process into different stages. They can identify and

explain the roles of participants, responsibilities of

management activities, processes, important events

and other key elements in different stages. Through

effective data management activities, the

corresponding model can also be optimized.

2 RESEARCH SIGNIFICANCE OF

PUBLIC SECURITY DATA

MANAGEMENT CAPABILITY

MATURITY MODEL

Under the background of continuous social

development and change, the public security situation

is becoming more and more complicated, and

traditional security accidents are characterized by

frequent occurrences and non-traditional security

threats, which will seriously affect social stability and

the level of economic development. From data

production to data analysis, it is necessary to carry out

data analysis and collation based on the demand of

security public decision. We should realize that this

process has the characteristics of long-term and

complexity, and the level of public security data

management can be improved through reliable data

information. In the process of developing and

managing public security data, it is necessary to

strengthen government regulation and guidance, and

He, Q. and Jiang, L.

Discussion on the Construction of Public Security Data Management Capability Maturity Model.

DOI: 10.5220/0011343900003437

In Proceedings of the 1st International Conference on Public Management and Big Data Analysis (PMBDA 2021), pages 321-326

ISBN: 978-989-758-589-0

321

fully tap the application value behind public security

data.

In 2015, China has put forward an action plan to

promote the development of big data, and different

provinces and cities in China are also carrying out big

data management according to the corresponding

plan. In the concrete work, we need to sort out the

public data and strengthen the data quality

management and research work. Building a unified

data management platform can improve the

efficiency of data sharing and play a certain role in

ensuring the comprehensive utilization rate of public

data. We need to pay attention to the scientific and

reasonable public security data management

mechanism according to the specific regional

characteristics in the process of public security data

management. Because of the different economic

bases in different regions, there are some differences

in the cognition of public security data management.

At present, China has not formed a unified path and

goal for the development of public security data

management, nor has it scientifically evaluated the

level of public security management, which leads to

the inability of relevant departments to optimize and

adjust relevant mechanisms according to the situation

of public security data management, and to a certain

extent, affects the formulation and implementation

effect of data management plans and solutions. In this

research process, we mainly analyze the capability

maturity model, and discuss the specific application

value of the capability maturity model in the process

of public security data management. Structured data

management plays a prominent role in determining

the evaluation method of public security data

management capability, which can provide clear

management capability improvement goals and

directions for government departments and related

institutions(Ye 2015).

3 CHARACTERISTICS OF

CAPABILITY MATURITY

MODEL

When building the capability maturity model of

public security data management, it is necessary to

fully grasp the characteristics of the capability

maturity model. The primary function of capability

maturity model is to evaluate the management

capability in the process of software development.

After the capability maturity model is put forward, its

basic structure remains unchanged (Figure 1), which

mainly includes key process areas, specific

objectives, specific practices, common objective,

common practice, common features and capability

levels (Xiong 2020). Among them, the key process

area is the problem that must be solved when realizing

the management goal. The original capability

maturity model consists of 22 key process areas, and

specific objectives and practices refer to specific

objectives and practices in a key process area.

Common objectives and common practices can be

applied in several key process areas. Each key process

area is organized according to public attributes,

including implementation regulations,

implementation capabilities, implementation

activities, measurement and analysis, and

experimental verification. In the research process of

capability maturity model, it includes five steps as

shown in Figure 2.

Figure 1: Schematic diagram of the capacity maturity

structure.

Figure 2: Capacity maturity model ladder.

4 ANALYSIS OF PUBLIC

SECURITY DATA TYPES

Public security data refers to all kinds of data

generated in the process of public security

governance. Generalized public security data

includes all kinds of data in all public security fields.

The main function of public security data is to reflect

the concrete phenomena of public security

governance activities, and to obtain the characteristics

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and laws of public security governance activities from

various data, so as to optimize and improve the

corresponding management decisions. The main

characteristics of public security data are huge

amount of data, low application value density,

diversification and obvious big data characteristics.

At present, there is no unified classification standard

for public security data, because the amount of public

security data is relatively large, and there are public

security data in different industries, different

organizations and different data terminals.

When studying public security data, there will be

some differences in the definitions of different

researchers: (1) Researchers think that the public

security data of cities mainly include different

categories of urban public basic data, social situation

and public opinion data, physical environment and

disaster monitoring data, urban operation data,

departmental business data, human behavior data,

emergency handling data and public security

knowledge data. Different categories cover different

types of specific data. (2) Some researchers directly

divide urban big data into sensor system data, user-

generated data, government data, private sector data,

art and humanities data and other mixed data. (3)

Some researchers believe that public security data

simply refers to national security big data. These data

are distributed in the information space, physical

space and social space where people and things are

highly integrated in various complex correlation

forms(Sun 2019).

Because public security in a broad sense refers to

all external environments and orders related to social

life security, including environmental security, public

health security, economic security, information

security, food security, production security, workplace

security and so on. The data generated in these fields

are all public security data. In this research, it is

necessary to scientifically evaluate the maturity of

public security data management ability from the

commonality of data in different security fields.

Public security data is mainly a mixed

environment formed by the integration of Internet,

communication network and sensor network,

including physical space, social space and virtual

network coupling space. The data spaces stripped

from these spaces can all be called public security data

spaces. Physical objects in space are the main carriers

of public security data, including data of key

infrastructure, road traffic structure and semi-

structured infrastructure, as well as unstructured

multimodal data such as environmental physical

parameters and videos sensed by large-scale sensing

devices in human living space. In addition, individuals

and organizations in social space are also the main

producers of public security data, including basic

demographic data, individual or group personality

characteristics, emotional representation, cognitive

decision-making and other psychological data and

behavioral data. Virtual network coupling space refers

to the data generated in the overlapping coupling of

network space, physical space and social space. The

main carrier of these data is the Internet or mobile

terminal devices, including data and information risk

data processed by basic networks and different types

of application systems in information construction, as

well as some unstructured and semi-structured data

such as news reports, forum posts and blog posts.

In a word, the sources of public security data are

complex and the number is huge, and its obvious

feature is that the data of different industries have

strong connections. Because the public security

governance activity itself is continuous, it determines

that the generation and acquisition of public security

data have strong continuity. For example, the business

systems of government departments will constantly

update the corresponding data. In addition, public

security data are complex, diverse and interrelated.

The data of different fields, different sources and

different structural types are relatively large in scale

and growing at a relatively fast rate. There is a certain

connection between public security data of different

fields, and public security governance activities

involve different departments, industries and fields.

Therefore, the generated public security data also have

obvious correlation. Public security data involves a

wide range of subjects, and the production

management and use of public security data involve

different participants such as government

organizations, enterprises, the public and researchers.

These data characteristics determine that the

management of public security data is extremely

complex and difficult.

5 CONSTRUCTION OF PUBLIC

DATA MANAGEMENT

CAPABILITY MATURITY

MODEL

5.1 Model Design

When building the maturity model of public security

data management capability, we must clearly grasp

the public security data management practice and key

practice processes. Based on this, the key process area

can ensure the effectiveness of the maturity model of

Discussion on the Construction of Public Security Data Management Capability Maturity Model

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public security data management capability, and

based on the maturity model, the level of public

security data management capability can be

scientifically divided. In CNKI, database data

supervision, data guarantee, data fusion and so on

should be used as key words to search for literature.

When searching documents, we should eliminate the

data with low correlation with public security data,

such as medical, financial and energy data, and

identify and sort out the documents highly related to

public security data management. After importing the

identified files into Nvivo software, extract and

encode the data. There are inconsistencies in the

codes, which need to be discussed in groups to

determine the final result. Data management practice

extraction is the key content that must be paid

attention to in the coding process. When extracting

data management practice, it is necessary to combine

similar contents, organize data management practice

into key practice processes, and form key process

areas based on key practice processes. In order to

ensure the application effect of the public security

data management capability maturity model, when

designing the model, we should bring the key

practices and key process areas into the model index

system and carry out the grading work. In this study,

it is necessary to explain the levels of capability

maturity, and accurately describe the characteristics

of different key process areas in each level to form the

classification of public security data management

maturity levels, as shown in Figure 3.

Figure 3: Schematic diagram of the public security data management capacity maturity level classification

5.2 Management Process and Practice

Construction

In the design of key process areas and key practices

of public security data management, we can use

Nvivo files for coding, summarize the key practices

of public security data management capabilities, and

combine similar practices to obtain integrated data.

According to the goal of key practice, four key

process area indicators can be determined, such as

data acquisition and quality control, data classified

storage and security management, data mining and

analysis, data opening and sharing. In the specific

process of information extraction and mining, it is

necessary to know about researchers and research

years, as shown in Table 1.

Table 1: Key process areas and key process research years and researchers.

Key process areas Key process Research years and researchers

Data acquisition and

quality control

Clear data source 2010 Zhao Chunyan, 2014Wen Bowei

Determine the data acquisition

metho

2012 Chen Beiqing, 2014 Tian Yuchi, 2016 Hu Yu

Determine the data collection

ecifications

2014 Wang Ting, 2018 Yang Jiangyong

Data acquisition

2008 Dong Rencai, 2014 Wang Ting, 2018 Yang

Jiangyong, Li Guanhua

Data quality management 2015 Li Weibin, 2018 Yang Jiangyong

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Table 1: Key process areas and key process research years and researchers (cont.).

Key process areas Key process Research years and researchers

Data classification,

storage, and security

management

Establish a data storage

latfor

2012 Du Hongyue, 2016 Hu Yu, Jin Hui

Data preservation 2013 Liu Jun, 2015 Wang Weibin, 2016 Hu Yu

Data security management 2013 Liu Jun, 2014 Tian Yuchi, 2018 Yang Jiangyong

Authorization management 2005 Xu Yonggang, 2016 Hu Yu, Zhang Shuai

Data backup 2005 Xu Wei, 2014 Zheng Xiufen

Data maintenance and update

2010 Zhao Chunyan

2016 Hu Yu, 2018 Li Guanhua

Determine the data standard

system

2015 Li Xiaohong, Wang Weibin, 2016 Hu Yu, 2017 Wu

Xianhua

Data classification

2010 Zhao Chunyan, 2015 Jin Hui, 2016 Zhang Shuai, Hu

Data mining and

analysis

Clear the data usage

uirements

2015 Deng Lan

Data analysis

2012 Du Hongyue, 2015 Wang Weibin, 2017 Wu

Xianhua, 2018 Yang Jiangyong

Visualization processing 2011 You Hong, 2013 Hu Pian, 2014 Wen Bowei

Data opening and

sharing

Fusion data 2008 Dong Rencai, 2014 Wen Bowei, 2017 Wu Xianhua

Build a shared platform 2010 Zhao Chunyan, 2012 Du Hongyue

Develop a data sharing

mechanis

2010 Zhao Chunyan, 2012 Du Hongyue

Complete data sharing 2014 Wen Bowei, Wang Ting, 2016 Hu Yu

5.3 Maturity Construction of Public

Security Data Management

Capability

After obtaining the key process areas, it is necessary

to build a maturity model of public security data

management based on the key process areas. Based

on the maturity level of capability maturity model, it

is considered that the practice of public security data

management, through temporary management to fine

planning, is constantly improving the formation

system in China. The characteristics of different key

process areas are different with different maturity

levels. First, in the initial stage, the public security

management system is relatively scarce, and the

whole management process has not been

scientifically defined, nor has a unified standard

management process been formulated. Public

security data is in a disorderly situation, with data

islands and low data utilization rate. Second, in the

repeatable stage, it has been possible to establish

basic system and procedural standards according to

public security data management. In addition, it is

necessary to optimize and adjust the data

management process based on the current situation of

public security data management, which improves the

standardization level of data management to a certain

extent, can carry out public security data management

according to certain rules and standards, and can meet

specific needs and ensure the application effect of

public security data. Third, the level has been defined.

This means that the public security data management

process is relatively perfect. In the process of public

security data management, its standardization is

relatively strong, and a data demand response

mechanism that can meet the requirements of public

security data management has been formed, which

can ensure that the public security data management

can meet the specific needs. Fourth, the management

stage. To determine the relevant indicators of public

security data management, and to ensure the quality

and efficiency of public security data management. At

this stage, the public security data management

mechanism is also relatively perfect, and the public

security data analysis model base has been

completed, and research and analysis work can be

carried out according to the public security data

management work. Comprehensive analysis of public

security data can quantify the analysis results of

public security data, thus supporting public security

management decision-making. Fifthly, in the

optimized stage, the public security data management

has a standardized process, and the management

quality is guaranteed. In addition, with the increase of

Discussion on the Construction of Public Security Data Management Capability Maturity Model

325

data utilization rate, data fusion and analysis can be

carried out in time according to the specific situation

of public security data, especially when dealing with

public crisis events, and its response speed is

relatively fast(Niu 2019).

5.4 Model Application

In the construction of public security data

management capability maturity model, it is

necessary to base on the specific situation of public

security data management in China. Comprehensive

research on key process areas such as key practices,

data acquisition quality control, data mining and

analysis, data opening and sharing, data classification

and storage, and security management, etc., and use

this as the main index to complete the construction of

public security data management capability maturity

model. After the completion of the construction, the

maturity level should be scientifically divided, and its

value is prominent in the process of model

application, mainly in the following aspects: First, the

maturity model of public security data management

capability can be used to scientifically evaluate public

security data management capability, and provide

more scientific and perfect data support and

corresponding information services for the

formulation of public security data management

scheme. In the application process of the model, key

process areas and key practices are important

indicators when establishing the model. Government

agencies or related organizations can make use of the

public security data management capability maturity

model to deeply analyze the situation of public

security data management, compare it with the

indicators in the model, and master the effect of

public security data management capability based on

the level division of the capability maturity model,

which can make relevant government agencies and

organizations clear the shortcomings in the process of

public security data management, and help promote

the healthy development of public security data

management. Secondly, the application of the model

can improve the standardization of public security

data management. The development stage defined in

the model itself belongs to the continuous

management promotion process, while different

organizations carry out data security management

based on the model, and take different development

stages as the main criteria for data management

planning of public security, which is conducive to

ensuring the standardization of data security

management. Third, we can compare and analyze the

quality of public security data management in

different institutions. For example, when evaluating

the public security data management capabilities of

different county and city governments, we can use the

key practice areas as the reference benchmark, and

through horizontal comparison and analysis, make the

institutions with low capabilities learn from those

with higher capabilities (Zhou 2020).

6 CONCLUSIONS

To sum up, the construction of public security data

management capability maturity model can provide

perfect information services for the government and

related organizations in public security data

management to a great extent. The key practices and

key process areas put forward in the application of the

model are important contents to ensure that the

capability maturity model can fully play its role.

However, in the application and research process of

this model, it is still in the preliminary exploration

and research stage, and more attention is paid to the

data creation process in the application of this model.

This requires an in-depth analysis of the current

situation of public security data management and

continuous improvement and optimization of the

capability maturity model according to the actual

capabilities of public security data management, so as

to provide more reliable information support for the

improvement of public security data management

capabilities.

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