This paper comprehensively combs the development trend of data governance standardization, standardization organization and typical data governance standards, and expounds the conceptual connotation and existing challenges of data governance standardization. Then it discusses the application of basic standardization methods in data governance and the supporting role of data governance in standardization, and puts forward suggestions for follow-up work.
Data has become a factor asset for governments and enterprises in the digital era, and data quality is one of the major tasks to build data asset. In this paper, the concept of data quality and the traditional “six dimensions” methodology are systematically reviewed, and a “business-centered authenticity” principle for data quality management is suggested and elaborated with practical cases. The paper also proposes an integrated data computing strategy of building accurate and credible data assets.
As social consensus, data has become a new driving force for economic and social development and digital transformation, while data quality has become an important factor affecting the value of data elements. In the field of e-government, the depth and breadth of the data application are gradually strengthening, and the problem of data quality has become the restricting factor of data deepening application. The article is based on the theory of data quality management, using the control over source data quality as a means, advances a method of data quality management based on intelligent data exploration, which is to activate data value through data quality management. The method can be used for reference in the work of e-government’s data quality management.
Under the background of accelerating the digital transformation of thousands of industries and the comprehensive arrival of the era of digital economy, the importance of data has been widely valued. At the same time, the problems of personal privacy protection and data security are becoming more and more serious. As a new exploration that could solve the dilemma of the realization of data value and the protection of data rights and interests, data trusts have attracted extensive attention at home and abroad, formed development ideas from two different perspectives of data governance and data capitalization, and accelerated from theory to practice. Combined with China’s legal system environment and the strategic orientation of digital economy development, this paper puts forward some ideas and suggestions for the development of data trusts in China in the future.
Based on the traditional method of asset evaluation, this paper fully consider shareable and other characteristics of data assets, takes the attributes of data quality and data application effect as the influencing factors, and proposes the monetization value calculation method applicable to data assets. And taking the data assets of EverBright Bank as the calculation object, it realized data asset value calculation.
In the face of the increasingly severe situation of data security, the state, local government, and industry have successively issued several laws and regulations, followed by a series of related review and rectification actions. The domestic data security has entered a new stage of strong supervision. In this context, it has become an industry consensus to improve the level of data security by building a data security governance system, and how to evaluate the effectiveness of the system’s construction has attracted the attention of all parties. Therefore, building a sound assessment framework of security governance capability plays an important role in grasping the common problems of data security, understanding the development of the industry, and discovering the practice benchmark in the industry.
In recent years, data security incidents have occurred frequently, which has damaged corporations’ interests and reputations. With the data security laws and regulations coming into effect, corporations have realized the importance and urgency of data security governance. Based on the observations of corporation data security governance evaluation in 2021, data security governance capabilities and trends of corporations are summarized by organizational construction, talent training, technical tools. Improvement opinions are provided as the reference to the public.
In the era of digital government,government departments have an increasing demand for data governance and higher requirements for specialization,real-time and individuation of data governance. Simple platforms and tools have the problem of high construction costs, difficult operation and low effects. From the perspective of government data governance services, this paper proposes a government data governance service model based on the government data resource system, which can quickly and efficiently respond to the differentiated needs of government data governance, helping the digitalization and intelligence of government business processes and service models.And four cases of the data governance service model in Jinan are introduced in detail.
In the era of digital economy, data becomes the core asset of operators.DataOps is an effective mode to release data value, and big data platform is the technical basis to realize DataOps. This paper sorted out the development of DataOps and big data platform, elaborated the connotation of DataOps, proposed the method of applying DataOps to the big data platform of operators, and constructed the framework of big data platform of operators based on DataOps.
In the digital age, data, as a factor of production, has had a profound impact on all walks of life. With the support of blockchain, 5G, artificial intelligence, cloud computing and other technologies, enterprises have comprehensive data, which is more conducive to insight into business opportunities, risk prevention and control, and enhance brand competitiveness and influence. It is imperative for large group enterprises with transnational or mixed operation to realize data integration and sharing within the group. However, in this process, they must strictly abide by national security, network security, regulatory requirements and the requirements of various domestic and foreign laws and policies such as personal information protection. It is easier to know than to do. Based on this, through the study of group data integration management, this article tries to explore the international and comprehensive large-scale group enterprises to carry out data integration and sharing legally feasible mode.
Head Internet technology enterprise, telecom operators, and system integrator have continued to invest more on the construction of city brain which is a most-focused domain and high-value part in the construction of new smart city. To begin with, the background of constructing city brain was analyzed together with the characteristics and trends of city brains arranged by enterprises. On this basis, the current predicament encountered in the construction of city brain in China was summarized. In response to it, suggestions were proposed for governments and enterprises to promote the construction of city brain from the perspective of supply and demand.
Digitization is reforming the employment ecosystem in an all-around way and expanding the existing theory of the employment ecosystem, which has triggered heated discussion on the “digitalization+” employment ecosystem. The “digitalization+” employment ecosystem in this article, is a phased product of the employment ecosystem in the digitalization process, and it is a relatively stable employment dynamic equilibrium state formed during the digitalization period. Data elements, digital space, digital technology, digital institutions, digital organizational power, digital culture, and many other factors constitute the “digitalization+” employment ecosystem. Any one of these factors affects the overall situation, and these factors jointly promote the evolution of the employment ecosystem. The “digitalization+” employment ecosystem presents some new features, such as the continuous expansion of jobs, more efficient allocation of labor resources, the emergence of new mechanisms of digital organization, the expansion of labor market radius, and the logical changes of the employment behavior. The “digitalization+” employment ecosystem follows a general law, that is, its development is from building, rapid development, frequent problems, to continuous improvement. Therefore, it is necessary for all participants to recognize the essence of the “digitalization+” employment ecosystem, respect its laws, constantly strengthen their responsibilities, and jointly promote the continuous improvement of the digital ecosystem.
Industrial Internet is a new generation of information and communication technology and manufacturing industry deep integration of key infrastructure, new application models and new industrial ecology, through the comprehensive interconnection of people, machines and things, to build a full factor, the whole industrial chain, the full value chain of comprehensive connectivity, data-driven industrial production manufacturing and service system, become the construction of national digital governance system and governance capacity modernization of an important infrastructure. Industrial Internet identity analysis system through the unique identification of physical and digital entities, to achieve “cross-enterprise-cross-industry-cross-regional-cross-country” identity data management and interaction, support Industrial Internet network connectivity, data sharing, is conducive to breaking through the difficulties of data governance, speed up the process of digital governance.
Digital Therapeutics combines diseases, data, and algorithms to help medical staffs monitor patient’s condition remotely. Meanwhile, it can be combined with drug therapy to improve efficacy, reduce treatment costs, and better manage diseases. This paper analyzes and summarizes the technical background, definition, categorization and typical application scenarios of DTx. On this basis, this paper further analyzes the current development status and challenges of the DTx industry and provides some suggestions for its future development from both the technical and policy perspectives.
The key of enterprise digital transformation is to build“Enterprise intelligent brain”based on data engine and technology engine. The“Digital intelligence brain”proposed in this paper includes a unified display center, a real-time command center, and a multidimensional interaction center in terms of functional modules. Supported by digital infrastructure, data engine, and technology engine, it adopts the forms of reasonable design, automatic arrangement, orderly presentation, management penetration, hierarchical management, and real-time command, so as to empower enterprise operation, customer service, marketing, ecological construction and other applications.
With the advent of the era of knowledge economy, the monetary value of patent is dominating, and patent rights is being used as an significant profit-making way of NPE as well. With the integration of injunction and litigation, the entities have been more pressed by NPE than ever, which makes adverse effect on advancement of our civil ICT industry, including the strangulation of the low profit of our civil industry, the high cumulative patent rate over the upper limitation, the harming on the capability of our civil innovation. Meanwhile, the occidental countries and regions are adjusting and refining their patent-related laws and systems from various aspects like legislation, enforcement, justice and etc., which makes the scope and boudary clear to apply law and provides better opportunities for the development and innovation of their industry. After all our country shall gradually change from the former passive defensive rule of law to the leading rule of law, and strengthen the legal regulation of NPE.