| Under the background of big data and global risk society,data-driven governance innovation has become an important issue,and using big data to remake social governance goes mainstream.China has incorporated the development and application of big data into the national strategy.Social data that represents and describes the status,degree and trend of social development,is not only an crucial part of the national big data resources,but also plays a constructive role in promoting the modernization of social governance.There has been a widespread recognition of the value of social data and strong demand for data intelligence.However,there exists many risks and challenges in applying social data to governance decision-making.The lack of social data governance results in the increase of decision-making cost but the decrease of governance efficiency.In view of the low efficiency of data governance in China,it is necessary to design a scientific and reasonable data governance mechanism based on a comprehensive understanding of the risks of social data,combining with the goal of social governance modernization and its demand for data resources,so as to improve social data governance to effectively reduce and avoid risks in data application and bring the value of data into full play.Through combing the existing research on social data risk and its identification methods,data risk dimensions,social data governance mechanism,etc,it’s found that lots of scholars studied the data risk composition and have proposed some data governance model as well as a series of mechanisms taking big data,enterprise data,scientific data and government data as research objects.However,there is a lack of systematic and specialized research on social data risks and its governance issues.Therefore,this study puts forward the issue of how to govern social data in the view of risk dimension,using a combination of theoretical analysis and empirical research,based on scientific theory such as Risk Society Theory,Synergy Theory,Data Life Cycle Theory,Stakeholder Theory,systematically analyze the risk factors and its multiple dimensions of social data applied to governance decision-making.Finally,facing the goal of social governance modernization,a model for improving the social data governance mechanism and the corresponding strategies are proposed according to the needs and governance deficiencies of social data in China.First of all,the study explores the composition of social data in China from two different criteria: the subject who generates the data and the field to which the data belongs.According to this,social data is deconstructed into data generated by governments,enterprises,institutions,social organizations,individuals and other subjects,covering finance,medical care,transportation,education,agriculture and other fields of social production and life.And it’s believed that social data is community-based,effect-correlative,time-sensitive and structure-complicated,and can provide multi-dimensional analysis perspectives and cross-border associations in governance applications,empowering forward-looking,intelligent and multi-agent participation in social governance,while the recognition of social data risk dimensions will have an impact on the accuracy,intelligence and synergy of governance.Secondly,the paper systematically investigates the needs of social data governance mechanism from two aspects of policy and practice.It condenses the requirements of social data attributes to realizing its governance function into data visibility,liquidity,usability,security,and high quality.By focusing on the policies on data sharing and open data,transaction and circulation,quality management,and security and privacy,combined with the investigation of the implementation of the policy and its effectiveness,and Shenzhen’s governance practices towards health data,it’s shown that more attention should be paid to encouraging and guiding such social forces as enterprises and social organizations to participate in data governance,data quality certification and compliance review,metadata and life cycle management and hierarchical data management,and there is a strong demand for governance mechanisms for cooperative governance system,ensuring data consistency,enhancing data visibility and ethics compliance and risk assessment,and so on.Then,on the basis of literature,typical cases and statistical data,this paper identifies the risks of social data and extracts the structure behind them.Through the content coding analysis of 122 critical documents and 12 typical cases of,this paper has screened 60 kinds of social data risks including poor data quality caused by variable omissions and sample deviations,and collaboration difficulties resulting from lack of consistency in data,from which 34 risk factors such as inconsistent structure of multi-source data and insufficient data openness are initially extracted,given that risk is a combination of risk factors and risk consequences.A questionnaire on the assessment of social data risk factors is subsequently launched and 589 valid questionnaires are finally obtained.Five dimensions of social data risk factors,namely data quality risk,data ethics risk,data acquisition risk,data cost risk and data security risk,are extracted by exploratory factor analysis after the fifth analysis.Finally,the dimensions of risk in social data application is applied to defining the principles and decision domain of social data governance,and a model for improving social data governance mechanism is constructed based on these.Under the dimensions of social data risk,we should pay attention to the legitimate rights and interests of stakeholders,strengthen multi-agent coordination and optimize system supply,and carry out governance activities centring on six decision domains,namely data principles,data quality,metadata management,data access and acquisition,and privacy,security and compliance.Based on the results above,beginning with clarifying the contents and interrelations of the four core components of principles,objectives,scope and implementation,a model for improving social data governance mechanism is built on the dimensions of social data risk.After explaining the main contents,features and functions of the model,and taking the actual needs of social data governance in China into further consideration,the paper details the content of model implementation from five aspects: governance structure,resource construction,operation safeguard,implementation guidance and public interest.Totally seventeen governance mechanisms,such as pooling national metadata resource under unified plan,preparing a checklist for social data governance are developed.This study draws the four valuable conclusions that in social data governance we should:(1)establish a good common cognitive to improve the coordination level and practical benefits of multiple subjects;(2)strengthen the control of multi-dimensional risk in social data governance,focus on the key and essential issues that cause data risks,continuously enrich the subject and means of prevention and control in the meanwhile;(3)promote the synergy of technology,management and policy to make them drive each other;(4)pay attention to the social allocation of governance costs and give full play to the resource advantages and subjective initiative of market players and professional institutions.As a systematic exploration of data governance issues in the risk dimension and social governance application scenarios,this research is expected to generate certain academic and application value by providing us with a reference to gaining a more sound understanding of social data and more accurate and effective social data governance,not only in theory and practice,but in reality and future.(Figure 7,Table 14,Appendix 2)... |
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