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    15 January 2023, Volume 9 Issue 1
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    STRATEGY RESEARCH
    Big data technologies forward-looking
    Hong MEI, Xiaoyong DU, Hai JIN, Xueqi CHENG, Yunpeng CHAI, Xuanhua SHI, Xiaolong JIN, Yasha WANG, Chi LIU
    2023, 9(1):  1-20.  doi:10.11959/j.issn.2096-0271.2023009
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    Major countries in the world attach great importance to the development of big data technology.China also puts big data as a national strategy, of great significance to develop in the long run.Big data technologies include data collection, transmission, management, processing, analysis, and application, forming a data life cycle as well as the data governance related to each procedure.Big data management, processing, analysis, and governance in four areas were seleceted, to identify the gap between China and the world.On the other hand, driven by diverse successful big data applications, the system architecture of computing technology is being restructured.From “computation-centric” to “data-centric”, fundamental computing theories and core technologies need to be redesigned, therefore a new type of big data system technology is becoming an important research direction.Against this background, four technical challenges and ten future development trends of big data technologies were aimed at identifying.

    TOPIC: METAVERSE AND BIG DATA
    Metaverse and Big Data
    2023, 9(1):  21-22.  doi:10.11959/j.issn.2096-0271.2023009-1
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    Rhythm dancer: 3D dance generation by keymotion transition graph and pose-interpolation network
    Yayun HE, Junqing PENG, Jianzong WANG, Jing XIAO
    2023, 9(1):  23-37.  doi:10.11959/j.issn.2096-0271.2023004
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    3D dance is an indispensable form of virtual humans in the metaverse.It organically combines music and dance art, which greatly increases the interest in the metaverse.Previous work usually treats it as a simple sequence generation task, but it is difficult to match the dance movements with the music beat perfectly and the quality of long sequence dance generation is difficult to be guaranteed.Inspired by the process by which humans learn to dance, a novel 3D dance framework “Rhythm Dancer”to solve the above problems was proposed.The framework first uses VQ-VAE-2 to encode and quantify the dances in a hierarchical way, which effectively improves the quality of dance generation.Then, a key movement transition map was created using the core dance movements on the rhythm points, which not only ensures that the generated dance movements fit with the music beat, but also increases the diversity of dance movements.To ensure smooth and natural connections between the core dance moves, a poseinterpolation network was proposed to learn the transition movements between key moves.Extensive experiments demonstrate that the framework not only avoids the instability and uncontrollability problems of long sequence generation, but also achieves a higher match between dance movements and music rhythms, reaching state-of-the-art results.

    Metaverse air pollutant concentration inference model based on digital twin technology
    Yifei PENG, Zhen YUAN, Xulong ZHANG, Guilin JIANG, Yujiang LIU
    2023, 9(1):  38-50.  doi:10.11959/j.issn.2096-0271.2023005
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    Air pollution is closely related to people's health and economic and social development.However, monitoring sites are sparsely distributed and cannot provide fine-grained air pollutant concentrations.In addition, the existing air pollutant concentration inference methods lack the ability to process relevant data in real time, so they have a hysteresis.To solve the above problems, a metaverse air pollutant concentration inference model based on digital twin technology was proposed.The model maped the real data into the metaverse space, and built a data warehouse to achieve real-time accurate inference of air pollutant concentrations through the construction of an air pollutant feature library.The experimental results show that the model can improve the accuracy and validity of air pollutant concentration inference.

    Design of the layered model of the metaverse based on computing network
    Zihang WANG, Xiangqun YU, Hongbiao SI, Simin FU, Xulong ZHANG, Shaoliang PENG
    2023, 9(1):  51-62.  doi:10.11959/j.issn.2096-0271.2023001
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    The metaverse is a process of virtualization and digitalization of the natural world, integrating various technologies.Virtual reality and blockchain are the underlying technologies for building the metaverse, but they are very different in data processing and computing power requirements.To solve the problems of data heterogeneity and computing power heterogeneity between blockchain and virtual reality, the concept of a ＆quot;meta-computing center＆quot; was described.The meta computing center, blockchain nodes, and edge servers formed a computing network in the hardware architecture.The meta computing center centrally processed the interaction between the virtual scene rendering data and virtual human objects.Digital assets and personal information were desensitized and stored on multiple distributed nodes using blockchain, and the edge server handled simple interaction.In terms of software architecture, a layered processing model was designed in combination with hardware architecture, and heterogeneous data such as model data and asset data were placed in different software layers for processing.Finally, the metaverse mall was designed based on the layered processing model, which provided some reference for future metaverse applications.

    Cloud-edge-end collaborative big data management for metaverse
    Rui ZHU, Hongzhi WANG, Shuangshuang CUI, Kaixin ZHANG, Yu YAN
    2023, 9(1):  63-77.  doi:10.11959/j.issn.2096-0271.2023011
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    With the increasing number of users in the metaverse, the data also increases accordingly, which brings challenges to the data management of the metaverse.Big data management techniques are essential to realizing the metaverse.Therefore, data management technology in the metaverse was discussed.The metaverse was decomposed into three levels cloud, edge, and end.The massive data in the metaverse was analyzed.The four challenges of data management in the metaverse were discussed, and the corresponding research routes were put forward from four aspects of data synchronization, data access, data model, and query optimization.

    Research on the construction of educational community from the perspective of metaverse
    Ye LIU, Wei CHENG, Yan LI, Yimeng YIN, Huijie SUN
    2023, 9(1):  78-86.  doi:10.11959/j.issn.2096-0271.2023002
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    With the continuous improvement of Internet technology, the metaverse has greatly impacted the development of the education field because of its immersive interaction scene.The characteristics of the educational metaverse community were analyzed first.Then the framework of the educational metaverse community was designed to support high-quality educational resource sharing in the community.To provide a reference for the development of education in the new era, challenges and strategies for the educational metaverse community were proposed finally.

    Research on the legal conundrums and regulation ideas of metaverse
    Bo HE
    2023, 9(1):  87-102.  doi:10.11959/j.issn.2096-0271.2023007
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    The rise and development of the metaverse have brought challenges to legal regulation.The metaverse is not a place outside the law, it also needs to abide by the law and ensure the correct operation in the legal orbit.Firstly, the development characteristics of the metaverse were summarized, such as technological, commercial, social as well as transnational, and the risks and responses were analyzed.Secondly, the main legal conundrums of the metaverse were analyzed including cybersecurity, personal information and privacy protection, data governance, virtual property, ecological governance, platform liability, and cybercrime.Finally, the idea of regulating metaverse development according to law was put forward, it was suggested to adhere to the principle of safe and controllable development, the appropriately advanced layout of legislation of metaverse, promote regulations in main areas through legislative means such as enactment, reform, abolition, and interpretation, and achieved good governance through good laws.

    Metaverse and big data: data insight and value connection in spatio-temporal intelligence
    Yang SHEN, Menglong YU
    2023, 9(1):  103-110.  doi:10.11959/j.issn.2096-0271.2023012
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    Metaverse realizes the simulation and feedback of the virtual world to the physical world by intellectualizing the data of space-time nodes.Big data is the core means to enhance human insight into the world.Starting from the concept deduction and definition logic of the metaverse, this study sorted out four different levels of conceptual dimensions of the metaverse and proposed a five-level data association model based on the nine-point thinking of big data insight.From the establishment of the metaverse system to the connection of multiple metaverse systems, this study explored the data generation, data collection, data analysis, and data value mining in the metaverse.This study analyzes the connection of space data, time data, and international data in the metaverse, and expects to better understand, describe and transform the world by studying the data insight and value connection in the metaverse.

    STUDY
    Data-Commerce-Ecosystem: data goods, data businessman and data commerce
    Yazhen YE, Yangyong ZHU
    2023, 9(1):  111-125.  doi:10.11959/j.issn.2096-0271.2023003
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    With the progress in the development of the data factor market, the concept of Data-Commerce-Ecosystem (DCE) has attracted wide attention.However, there has been little discussion on the connotation of DCE as well as its role and responsibilities in the modern-day economy, which hinders the formation of a data trade ecosystem.Possible categories of contemporary data goods, data businessmen, and data commerce, the proposed definitions of said concepts were discussed.Information goods, digital goods, and data goods were incorporated into the concept of data goods.Data businessmen were categorized into three groups based on their different commerce models, which were data suppliers, data service providers, and data commodity traders.Several DCE models were summarized, which were the self-produceand-market model, operation platform agent model, and data marketplace model.These discussions enrich the connotation of DCE and in turn provide theoretical support for the development of the data factor market.

    A hot-update-aware optimization to the query of LSM-Tree
    Qingyin LIN, Zhiguang CHEN
    2023, 9(1):  126-140.  doi:10.11959/j.issn.2096-0271.2022049
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    Key-value stores based on LSM-Tree have been widely used.LSM-Tree gains excellent write performance by collecting updated data in memory and then flushing data into storage in batches.However, in LSMTree-based key-value stores, old data generated by update operations will not be eliminated immediately from the storage system, resulting in a large amount of invalid data accumulated in the entire storage system, which will eventually significantly reduce the read performance of key-value stores.For the above problems, an active compaction method was proposed.By recording the history information of updated key-value pairs, recognizing hot-updated keys, finding SSTables that contain a large amount of invalid data in the storage system, and triggering compaction as soon as possible to clear much more invalid data, the proposed method could reduce write amplification and improve the read performance of LSM-Tree based key-value stores.Experiments showed that this method could reduce the average read latency of LevelDB by 65.2%, 99% read tail latency by 69.4%, and write amplification by 71.4%.

    Trajectory differential privacy protection method based on exponential mechanism
    Huicong JIAO, Wenju LIU, Ze WANG
    2023, 9(1):  141-152.  doi:10.11959/j.issn.2096-0271.2022042
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    A trajectory differential privacy protection method based on exponential mechanism was proposed, aiming at the problem of privacy disclosure caused by ignoring semantic information carried by location points in traditional trajectory data protection.For the privacy disclosure caused by the dual attribute information of geographic features and semantic features of location, an available scoring function for location points was designed according to the characteristics of the index mechanism in differential privacy.And the function randomized the output to protect the trajectory effectively privacy.This scheme could reduce the size of data sets while ensure location privacy, prevent semantic background inference attacks and improve data availability.Experiments were carried out on real trajectory data sets, and the experimental results showed that the proposed method not only effectively protected the privacy of the user's stay area location, but also effectively improved the data availability while ensured the privacy intensity.

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