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    Research on the development path and countermeasures of data element value
    Yunlong YANG, Liang ZHANG, Xulei YANG
    Big Data Research    2023, 9 (6): 100-109.   DOI: 10.11959/j.issn.2096-0271.2022080
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    Based on the development of data element marketization at home and abroad, the development path and characteristics of data element value in foreign countries were expounded.The current situation of China's data element market in terms of transaction market and application scenarios was summarized.In view of the current development of China's data element market, combined with China's data element market environment and development characteristics, through the construction of a data element market model with Chinese characteristics, we can speed up the release of data element value.

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    Overview of observational data-based time series causal inference
    Zefan ZENG, Siya CHEN, Xi LONG, Guang JIN
    Big Data Research    2023, 9 (4): 139-158.   DOI: 10.11959/j.issn.2096-0271.2022059
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    With the increase of data storage and the improvement of computing power,using observational data to infer time series causality has become a novel approach.Based on the properties and research status of time series causal inference,five observational data-based methods were induced,including Granger causal analysis,information theory-based method,causal network structure learning algorithm,structural causal model-based method and method based on nonlinear state-space model.Then we briefly introduced typical applications in economics and finance,medical science and biology,earth system science and other engineering fields.Further,we compared the advantages and disadvantages and analyzed the ways for improvement of the five methods according to the focus and difficulties of time series causal inference.Finally,we looked into the future research directions.

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    A measurable technical form of data is needed to include data assets in accounting statements
    Big Data Research    2023, 9 (6): 184-187.   DOI: 10.11959/j.issn.2096-0271.2023075
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    Digital transformation service platform:enhancing enterprise competitiveness in a new competitive situation
    Yazhen YE, Yangyong ZHU
    Big Data Research    2023, 9 (3): 3-14.   DOI: 10.11959/j.issn.2096-0271.2023029
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    With the improvement of data abilities and the development of emerging technologies, there are profound changes occurring in economic patterns and competitive structure of industries.In order to better respond to future opportunities and challenges, and to improve competitiveness of enterprises in new situations, it is necessary to understand and master the knowledge of digital transformation.The new competitive situation was discussed in which traditional enterprises would gradually be replaced by digital-transformed ones, digital transformation was differentiated from digitalization.Main challenges facing traditional enterprises while undergoing digital transformation were pinpointed, which were the lack of funds, talents, data and consciousness.A digital transformation service platform oriented to new competitive situation was proposed, which provided a feasible solution to enhancing enterprise competitiveness and conducting digital transformation.

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    Digital transformation in higher education:a systematic review
    Haihong QIAN, Maoyi WANG, Yun XIONG
    Big Data Research    2023, 9 (3): 56-70.   DOI: 10.11959/j.issn.2096-0271.2023032
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    Promoting digital transformation becomes the key to achieving high-quality development of education.Based on the survey of the current situation of education digitalization, the essence, development, and related techniques of education digitalization transformation were analyzed.The challenges faced by the digital transformation of higher education in China were analyzed and suggestions on education and management from the perspectives of data, technology, and talent were presented.The results to explore solution on the digital transformation of higher education can provide reference to promote the digitalization of education.

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    Industrial digital transformation:research onfault diagnosis methods
    Biao YANG, Yun XIONG, Ling FU, Weifeng XU, Jing LI
    Big Data Research    2024, 10 (1): 110-126.   DOI: 10.11959/j.issn.2096-0271.2023041
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    Industrial digitalization is an important way for industrial transformation and upgrading of China's industry, and digital transformation has become an important trend in the development of China's industry.The reliability and stability of industrial systems play an important role in the high quality and sustainable development of industrial production.Failures affect the operation of industrial systems and even cause major safety accidents and economic losses.To deal with this problem, fault diagnosis technology has emerged and gradually developed.Efficient and high-quality fault diagnosis digital technology has become a key technology for industrial digital transformation.The research progress of digital methods of fault diagnosis in industry were analyzed.According to the development characteristics, three stages were divided, including domain experience-led modeling methods, data-driven digital methods combining with domain experience, and data-driven digital methods combining with interpretability.Focus on the basic ideas and characteristics of the methods in each stage, the future research directions were discussed, and the references were provided for promoting industrial digital transformation.

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    Generative AI empowered metaverse organisms: prospects and challenges
    Hao WANG, Yushan PAN, Yi PAN
    Big Data Research    2023, 9 (3): 85-96.   DOI: 10.11959/j.issn.2096-0271.2023033
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    The metaverse has been discussed in fields such as medicine, manufacturing, finance, education, and public services, but the application scenarios based on virtual reality have not truly achieved the "real-virtual-real" loop interaction method.Its interaction mode has also not truly given the digital world the same consciousness and perception as the physical world.Taking medicine as a case study, the prospective applications and challenges of generative artificial intelligence models in metaverse organisms were explored, including digitizing biological cells, and building connections between digitized cells and digital neurons, in order to promote metaverse life forms to have perception and biochemical reactions consistent with the physical world, thereby empowering the development of the medical field.In response to the current advantages and disadvantages of the metaverse and generative artificial intelligence models, the clever design of human-machine collaboration mechanisms was discussed to promote conscious interaction between humans and metaverse organisms in medicine.

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    Data valuation approach and application in view of data full lifecycle
    Dongqing LI, Yinxiao LIU, Lei DENG, Mingyang LI
    Big Data Research    2023, 9 (3): 39-55.   DOI: 10.11959/j.issn.2096-0271.2023044
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    Data asset valuation is the foundation of modern data asset management, operation, and data circulation.Based on the theory of the data full lifecycle, starting from first principles, single data asset table was evaluated by assessing their cost, data management, and data application value.Using technologies such as data warehousing and graph algorithms, the cost value of a single data asset table was accurately calculated by using a layer-by-layer allocation method and inheriting the lineage path.Then, the non-economic factor weight of data asset was obtained by using the analytic hierarchy process, and the value of data asset was obtained through a ladder evaluation.Finally, verifies the rationality and feasibility of the new method was verified through an example.

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    Data Assetization and Digital Transformation
    Big Data Research    2023, 9 (3): 1-2.   DOI: 10.11959/j.issn.2096-0271.2023029-1
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    Big data and computing models
    Guojie LI
    Big Data Research    2024, 10 (1): 9-16.   DOI: 10.11959/j.issn.2096-0271.2024017
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    At present, artificial intelligence continues to heat up.Large language models have attracted much attention and set off a wave of enthusiasm around the world.The success of artificial intelligence is not essentially a "miracle" of large computing power, but a change in computing models.Firstly, this paper affirms the fundamental role of data in AI, and points out that synthetic data will be the main source of data in the future.Then, this paper reviews the development of computing models, highlights the historic competition between neural network models and Turing models.We points out that the important hallmark of large language models is the emergence of intelligence in machines, emphasizes that the essence of large language models is "compression", and analyzes the reasons for the "illusion" of large language models.Finally, we call on the scientific community to attach importance to large scientific models in "AI for research(AI4R)".

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    Research on the internal logic and solution of the “Channel Computing Resources from the East to the West” project
    Nannan TONG, Dong CHEN, Huiying LI, Honglin ZHU
    Big Data Research    2023, 9 (5): 9-19.   DOI: 10.11959/j.issn.2096-0271.2023055
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    The "Channel Computing Resources from the East to the West" project is a major strategic project to build a balance of computing resources and on-demand scheduling in China's territorial space.Since the full launch of the Chinese"Channel Computing Resources from the East to the West" project construction, a series of problems have been exposed on many different fields, such as the supply side, demand side, energy side, technology side, and mechanism side.It is urgent to re-analyze and define the internal logic of the "Channel Computing Resources from the East to the West"project from a theoretical level.The internal logic of "Channel Computing Resources from the East to the West", that is, the infrastructure of Chinese computing, was analyzed from different perspectives such as economic form, technological trend, technological competition, and cost-benefit.It also proposed to build a new type of infrastructure for the Chinese national computing network, called computing NET, and build a national computing NET construction path from the aspects of policy layout, network direct connection, technical support, and mechanism innovation.

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    Application of big data technology in data security governance
    Wei CHENG, Cheng MA, Jie LING
    Big Data Research    2023, 9 (6): 3-14.   DOI: 10.11959/j.issn.2096-0271.2023074
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    Facing the challenges of data security governance in the new situation and following the technological development trends in the field of data security, in response to the prominent issue of identifying key authorized personnel in the practical application of data security governance in large state-owned enterprises, this article proposes a key authorized personnel identification technology based on graph algorithm, which can discover potential authorization influencing factors in the system and measure the weight influence of different meanings from multiple perspectives, The recognition results have strong interpretability.Aiming at the problems of user and entity behavior anomaly detection in data security governance, this paper proposes a user and entity behavior anomaly detection method based on the generative adversarial network.The experimental results show that the accuracy, recall rate and average F1-score of the proposed method are better than the comparison baseline model method.A data security platform has been designed and developed.The platform has played an important role in reducing data security risks, assisting enterprise compliance construction, promoting data development and utilization, and has been applied in multiple data centralized management projects.It can meet the needs of big data processing in security scenarios, and has good application and promotion value.

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    A preliminary study on the construction ideas of"Channel Computing Resources from the East to the West" national integrated collaborative data security protection system
    Honglin ZHU, Qiang GUO, Beining SHOU
    Big Data Research    2023, 9 (5): 140-149.   DOI: 10.11959/j.issn.2096-0271.2023065
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    A number of problems faced by the construction of security protection capacity of the "Channel Computing Resources from the East to the West" project were analyzed, such as systematic layout, coordinated organization and promotion, and unified standards and norms, then the idea of building a nationwide integrated and coordinated data security protection system was proposed on the basis of that.

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    Analysis and research on the strategy and problems of “Channel Computing Resources from the East to the West”
    Yong SHI, Gang KOU, Biao LI
    Big Data Research    2023, 9 (5): 3-8.   DOI: 10.11959/j.issn.2096-0271.2023054
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    In March 2021, the “14th Five-Year Plan” was officially released, accelerating digital development and building a digital China is the goal of the future digital economic development model.As the basis of the digital economy, the state has issued a number of regulations to overall plan and promote the integration of big data centers and the overall construction of computing hub nodes to serve the development of the digital economy.In order to show the development status and related reasearch of the eight nodes in detail,the special issue of“Channel Computing Resources from the East to the West”of Big Data Research was specially prepared to analyze the characteristics of various regions and a series of problems.At the same time, based on the research results and research content, a number of suggestions were put forward: from the six aspects of local construction and employment income balance, network infrastructure construction, government guidance and marketization, big data independent hardware and software evaluation system, foreign data exchange and supervision, and talent team training.The found problems and corresponding suggestions were put forward to speed up the implementation of national integrated big data center with high quality.

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    Big Data Security and Privacy Computing
    Big Data Research    2023, 9 (6): 1-2.   DOI: 10.11959/j.issn.2096-0271.2023074-1
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    Channel Computing Resources from the East to the West
    Big Data Research    2023, 9 (5): 1-2.   DOI: 10.11959/j.issn.2096-0271.2023054-1
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    A survey of expressive speech synthesis
    Haobin TANG, Xulong ZHANG, Jianzong WANG, Ning CHENG, Jing XIAO
    Big Data Research    2023, 9 (6): 53-71.   DOI: 10.11959/j.issn.2096-0271.2022082
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    Speech synthesis is a hot research topic in the field of speech, language and machine learning, which aims to synthesize understandable and natural speech for a given text.It has a wide range of applications in industry.One of the goals of speech synthesis is to make the synthesized speech natural, and there is still a lot of room for improvement in emotion, prosody and other aspects of speech synthesis.A comprehensive survey of expressive speech synthesis was conducted with the aim of better understanding current research status and future trends.A comprehensive summary, comparison and analysis of emotion-based and prosodic speech synthesis in recent years were given.Firstly the traditional way and bottleneck of common speech synthesis were introduced, then expressive speech synthesis was introduced and the benefits of expressive speech synthesis in the aspects of emotion and prosody were described.Finally, the prospect and summary of expressive speech synthesis were presented.

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    Data central-platform: architecture and practice
    Xindong WU, Zeyu YING, Shaojing SHENG, Tingting JIANG, Chenyang BU, Zan ZHANG
    Big Data Research    2023, 9 (6): 137-159.   DOI: 10.11959/j.issn.2096-0271.2023034
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    A data central platform positions the data of an entity-be it a corporate entity, institutional body, or governmental department-as a pivotal strategic asset.It's a management mechanism that spans from data collection to processing and application, aiming to improve data quality, achieve extensive data sharing, and ultimately maximize the value of the data.A definition for data central-platforms was provided, and a generic architecture was presented along with the core technologies and functions of physical management, logical management, data asset management, data services and information security management.Finally, taking the construction of Huapu system as an example, a realization of the data central platform, which is geared towards genealogical big data and integrated with the HAO intelligence model, was introduced-Huapu Central-Platform.

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    Industrial analysis and thinking based on “data policies”
    Qinbo BI, Zhuting PAN
    Big Data Research    2023, 9 (5): 174-184.   DOI: 10.11959/j.issn.2096-0271.2023036
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    The three “data policies” were cross-interpreted and several thoughts on data industrial development from the perspective of data industry development trend, user data cognition, the scientific innovation and technology application on data industry were put forward.The authors believe that the development of both data industry and the industries who use data as key factor will accurately ignite the tipping point of economic development.Firstly, the acceleration impact of “data policies” on industrial development was discussed - data industry and data security industry will benefit from the “data policies” and became the backbone and main venue of high-quality development and empower the real economy.Secondly, the impact of “data policies” on user data cognition was expounded, which was helpful to understand the value symbiosis relationship between data factor and data security, establish the integrated governance cognition of data factor and data security, explore new ideas, new mechanisms, and new methods of data operation.Finally, the impact of “data policies” on technology and academic research around data circulation domain was described.It is necessary to adhere to the principle of “demand-driven, business-driven and practice-oriented” to achieve relevant technical breakthrough and strengthen technical weakness on supply side, furthering improve the supply capacity of scientific and technology innovation.

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    A survey on digital content generation, detection, and forensics techniques
    Juan CAO, Yongchun ZHU, Peng QI, Ziyao HUANG, Tianyun YANG, Zhengjia WANG, Yuyan BU
    Big Data Research    2023, 9 (5): 150-173.   DOI: 10.11959/j.issn.2096-0271.2023066
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    In recent years, the technology of digital content generation has been greatly developed, and the detection and forensic technology of digital content are facing new challenges.This paper firstly introduced digital content generation technology from three aspects: large natural language model, visual generation technology, and multimodal generation technology.Secondly, it introduced digital content detection technology from three aspects: generated text detection, generated image detection, and generated audio and video detection.Thirdly, it introduced digital content forensics technology from two aspects: utilizing fact ual information and forging traces.Then, this paper introduced the application scenarios of these techniques.Finally, it prospected the future work in this research field, and pointed out several directions that need to be focused on.

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    Research on algorithm and application risk and its governance
    Jingwen LI, Yawen LI
    Big Data Research    2023, 9 (3): 140-149.   DOI: 10.11959/j.issn.2096-0271.2023028
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    With the rapid development and in-depth application of information technology, algorithms are widely used in transportation, medical care, e-commerce, information services, public management and other fields, but their own data dependence, logical black box and general purpose characteristics also bring about data abuse in algorithm applications, algorithm discrimination in public management, algorithm manipulation in information services, algorithm collusion in market competition.In order to deal with the problems caused by the application of algorithms, countries have actively taken measures to strengthen the governance of algorithm applications.To promote the effective use of algorithms and strengthen algorithm governance, we need to further strengthen top-level design, improve governance pattern, enrich governance means, strengthen international coordination, and constantly improve the algorithm governance system.

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    Human avatars synthesis technologies: a survey
    Yimin DENG, Xulong ZHANG, Shijing SI, Jianzong WANG, Jing XIAO
    Big Data Research    2023, 9 (3): 114-139.   DOI: 10.11959/j.issn.2096-0271.2022081
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    Nowadays, the demand for efficient human avatars modeling is becoming increasingly urgent since metaverse has attracted more and more attention.Creating human avatars from human image datasets has always been a popular topic in the field of computer vision.3D human avatars synthesis can be regarded as a sub-module of 3D reconstruction focusing on reproducing the complex articulated body and surface details of human.A comprehensive survey of the literature related to the human reconstruction in recent years was conducted, including the work of full-body avatars, talking-head and clothing modeling.By analyzing and summarizing existing work, human avatars synthesis technologies were divided into five categories: mesh-based methods, image-based methods, voxel-based methods, implicit methods and hybrid methods due to the features of their pipelines.Firstly, the basic principles of them were introduced respectively.Secondly, the realization based on related work was discussed and then the advantages and disadvantages of methods respectively were pointed out.Thirdly, the datasets and metrics for model quality evaluation were introduced.Besides, an overview of various applications was given.Finally, the future directions of human avatars synthesis technology were prospected to synthesize high-quality, high-fidelity and low-latency human avatars.

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    Four issues to consider in building a computer system supporting large model training
    Weimin ZHENG
    Big Data Research    2024, 10 (1): 1-8.   DOI: 10.11959/j.issn.2096-0271.2024016
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    There are three types of computer systems that support large model training, among which the ecosystem based on domestic AI chip systems is not very good.To change this situation, it is necessary to develop 10 key software such as AI compilers and parallel acceleration.Moreover, systems based on supercomputers require good software and hardware collaborative design to better serve large model training.This article proposes a 4-point balanced design for building the infrastructure of a large model to ensure system performance, reliability, and scalability.

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    “Channel Computing Resources from the East to the West” of Qingyang cluster at Gansu hub:current status and prospects
    Huacun WANG, Boxia LIU, Yifei CHOU, Honglin ZHU
    Big Data Research    2023, 9 (5): 111-133.   DOI: 10.11959/j.issn.2096-0271.2023063
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    The purpose of the paper is to report on the development status of the Qingyang cluster of the Gansu Hub of the "Channel Computing Resources from the East to the West", to find out the existing problems, to look forward to the development prospects, and to accelerate the pace of the construction of the Qingyang cluster of the Gansu Hub.Literature research and field research methods were used to investigate and analyze the characteristic advantages, achievements, challenges and problems of the Qingyang cluster, and finally to look forward to the prospects for the construction of the Qingyang cluster.Suggestions were made: deploy from the national, provincial and cluster levels, through the implementation of industrial innovation and development period, industrial ecological enhancement period, industrial highland casting period three-step strategy, to complete the "seven strategies" tasks, focusing on the development of the "Channel Computing Resources from the East to the West" core, derivatives, empowering the "three industries".It will complete the tasks of "seven strategies", focus on the development of "Channel Computing Resources from the East to the West" core, derivation and empowerment industries, the formation of "three systems" of smart computing, intelligence and smart production, and the establishment of a "green, scientific and technological, and safe" smart park.

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    Sichuan’s strategic positioning and strategy research under the "Channel Computing Resources from the East to the West"
    Biao LI, Shaokun LI, Gang KOU, Xingtong CHEN, Xunfang ZHUO
    Big Data Research    2023, 9 (5): 20-31.   DOI: 10.11959/j.issn.2096-0271.2023056
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    The construction of the Sichuan "Channel Computing Resources from the East to the West" hub is an important component of the national integrated big data center innovation system.As a pivotal node tasked with both "East Number" and "West Calculation," its development holds unique significance.Accordingly, leveraging Sichuan Province's comparative advantages in industrial systems, energy endowments, computing cost, and scientific and educational talents, this study systematically analyzed the strategic positioning and development strategies of Sichuan in the context of "Channel Computing Resources from the East to the West".Focusing on the competitive relationships between Sichuan and other eastern and western nodes, as well as Chongqing, it addressed key issues and proposes recommendations, including coordinated positioning for development, efficient computing capacity absorption, and optimization of electricity pricing mechanisms.

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    An overview of Caideng metaverse research
    Yadong WU, Jiaming CHEN, Yan LUO, Xuefeng WANG, Dechun HUANG, Chao NI, Jiming LAN, Suiqun LI, Weihan ZHANG, Wei DAI
    Big Data Research    2023, 9 (3): 97-113.   DOI: 10.11959/j.issn.2096-0271.2023035
    Abstract161)   HTML20)    PDF(pc) (6262KB)(172)       Save

    As an emerging concept, metaverse has been widely concerned by the government, media, enterprises and academia.The technology and industrial applications of the metaverse have gradually become an important part of the digital economy.Chinese lantern, also called Caideng, is a national intangible cultural heritage.The concept of the Caideng metaverse was put forward for the first time.The combination of metaverse technology and the Caideng industry provided a new idea for the digital transformation and upgrading of the traditional Caideng industry.The current development status of Caideng, Caideng metaverse technology and application scenario were analyzed.The technical system supported by the six layers structure of the Caideng metaverse was proposed, and the application scenarios of the Caideng metaverse in festivals, games, commerce, night scenes, cultural and creative fields were analyzed.The new mode of the integration and development of the Caideng industry enabled by the technology of the metaverse was discussed.The three development stages of the Caideng metaverse were prospected.Caideng metaverse technology will enable users to experience more naturally and conveniently and interact with the Caideng world of virtual reality integration.

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    Research on data pricing model based on data market type
    Hongrun REN, Yangyong ZHU
    Big Data Research    2023, 9 (4): 116-138.   DOI: 10.11959/j.issn.2096-0271.2023052
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    The market is the process of establishing product prices, and the methods of establishing prices in different markets are different.The pricing model of product is an abstraction of the process of establishing product prices in the market.At present, the market demand for data has been formed, but an effective data market has not yet been formed and data pricing is still in the state of exploration.Most of the existing data pricing models are designed for some specific data transaction scenarios, rather than for specific types of data markets.This paper considers the economic market types of the data market, and divides the current data market into five data market types from the perspective of economics:monopoly market, monopsony market, oligopoly market, centralized perfect competition market and decentralized perfect competition market.Existing data pricing models are summarized into corresponding data market types.By analyzing the dependence relationship between data market types and data pricing models, the "market type principle" of data pricing is proposed to provide theoretical guidance for the construction of data element markets and its data pricing.

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    Research on digital transformation evaluation of small and medium-sized enterprises and regional differences in China
    Xu FENG, Hao CAO, Yang HU, Xiuqin WANG, Haoxiang ZHANG, Duanxin LING
    Big Data Research    2023, 9 (3): 168-180.   DOI: 10.11959/j.issn.2096-0271.2023045
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    Based on the provincial data of 2021 in China, an evaluation model for the digital transformation of small and mediumsized enterprises (SMEs) was constructed from five aspects: policy, facility, service, input, and effectiveness.And the AHP and entropy weight method was used to set index weight, the scoring method was used to standardize index data, and then the score of digital transformation of SMEs in 31 provinces were calculated.The score shows that there are obvious regional differences in the digital transformation of SMEs in China.The comprehensive index in the east region is the highest, and the central, western, and northeastern regions decrease successively, and are all lower than the national average.The comprehensive index has a significant positive correlation with export volume, and the correlation is higher than the correlation with GDP; the “policy” index takes the lead in the five sub-indices, and the “input” index is relatively lower.In this regard, four suggestions were put forward to promote the digital development of SMEs in China:strengthening digital financial support, lowering the threshold for using digital facilities, improving digital transformation service support, and strengthening the supply of digital workforce.

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    Data pipeline model: exploration of the overthe-counter form of streaming data
    Hongrun REN, Yangyong ZHU
    Big Data Research    2023, 9 (3): 15-28.   DOI: 10.11959/j.issn.2096-0271.2023031
    Abstract156)   HTML48)    PDF(pc) (2587KB)(337)       Save

    The current exploration of data element market construction mainly focuses on the construction of data trading venues, while the streaming data market refers to the market in which data suppliers continuously and quickly supply specific data to data users.Streaming data is not suitable for transactions in the data trading venues, so the over-the-counter trading model of streaming data needs to be explored.After studying the current operation status of the streaming data market, it was pointed out that market disorder and insufficient regulatory tools were the main problems, and a data pipeline model for the over-the-counter streaming data market was proposed, including pipeline circulation elements (data pipeline, data factory, data supply chain), market regulation elements (data meter, quality sampling device, compliance auditing device), etc.The technical feasibility of the data pipeline model was demonstrated, and it provided theoretical and technical support for the construction, regulation and supervision of the over-the-counter data market.

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    Mechanism and path of the national computing hub in the Yangtze River Delta enabling digital transformation of the manufacturing industry
    Yezheng LIU, Lihua HUANG, Yangyong ZHU, Jianshan SUN, Jingda SONG
    Big Data Research    2023, 9 (5): 61-77.   DOI: 10.11959/j.issn.2096-0271.2023059
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    The Yangtze River Delta is the source of national innovation with the most concentrated advanced manufacturing industry, the solidest development foundation, and the most active and potential innovative economy.The construction of a national computing hub node in the "Channel Computing Resources from the East to the West" project is great significance to accelerate the upgrading and transformation of the advanced manufacturing industry in the Yangtze River Delta.Therefore, this paper explored the logical mechanism, practical challenges and development path of the digital transformation of manufacturing industry enabled by the national computing hub node in the Yangtze River Delta based on the current difficulties and problems encountered in the digital transformation of the manufacturing industry, with a view to promoting the transformation and upgrading of manufacturing industry and the green and high-quality development of the Yangtze River Delta region.

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