Abstraction of Data Elements of Clinical Symptoms in Chinese Medicine

This report analyzes the existing problems in terminology referring to clinical symptoms of traditional Chinese medicine(TCM)from the viewpoint of data sharing and elaborates the necessity of establishing a standard directory of clinical data elements of TCM.We evaluated the principles and methods of data element extraction according to the status quo of the clinical information system and characteristics of symptoms for TCM and consequently proposed a three-layer model for optimal extraction.

Thoughts About Paths for Digitization of Traditional Chinese Medicine-Refined Data Elements

For digitalization of traditional Chinese medicine(TCM),research is being conducted on objectivization of diagnosis and treatment,mathematical models of TCM theories,and application of modern information technology to digitize the vast amounts of existing information.However,the author believes that TCM practitioners should first conduct a systematic and comprehensive refined analysis on the knowledge of TCM and unify data elements used in computer intelligence to avoid ambiguity.Thus,we must overcome the epistemological constraints and carefully analyze the relationship among data elements to achieve systematic results and administer TCM appropriately.

Data Component:An Innovative Framework for Information Value Metrics in the Digital Economy

The increasing dependence on data highlights the need for a detailed understanding of its behavior,encompassing the challenges involved in processing and evaluating it.However,current research lacks a comprehensive structure for measuring the worth of data elements,hindering effective navigation of the changing digital environment.This paper aims to fill this research gap by introducing the innovative concept of“data components.”It proposes a graphtheoretic representation model that presents a clear mathematical definition and demonstrates the superiority of data components over traditional processing methods.Additionally,the paper introduces an information measurement model that provides a way to calculate the information entropy of data components and establish their increased informational value.The paper also assesses the value of information,suggesting a pricing mechanism based on its significance.In conclusion,this paper establishes a robust framework for understanding and quantifying the value of implicit information in data,laying the groundwork for future research and practical applications.

Finite Element Simulation of Flexible Roll Forming with Supplemented Material Data and the Experimental Verification

Flexible roll forming is a promising manufacturing method for the production of variable cross section products. Considering the large plastic strain in this forming process which is much larger than that of uniform deformation phase of uniaxial tensile test, the widely adopted method of simulating the forming processes with non-supplemented material data from uniaxial tensile test will certainly lead to large error. To reduce this error, the material data is supplemented based on three constitutive models. Then a finite element model of a six passes flexible roll forming process is established based on the supplemented material data and the original material data from the uniaxial tensile test. The flexible roll forming experiment of a B pillar reinforcing plate is carried out to verify the proposed method. Final cross section shapes of the experimental and the simulated results are compared. It is shown that the simulation calculated with supplemented material data based on Swift model agrees well with the experimental results, while the simulation based on original material data could not predict the actual deformation accurately. The results indicate that this material supplement method is reliable and indispensible, and the simulation model can well reflect the real metal forming process. Detailed analysis of the distribution and history of plastic strain at different positions are performed. A new material data supplement method is proposed to tackle the problem which is ignored in other roll forming simulations, and thus the forming process simulation accuracy can be greatly improved.

Robust Element-Wise Empirical Likelihood Estimation Method for Longitudinal Data

For the regression model about longitudinal data, we combine the robust estimation equation with the elemental empirical likelihood method, and propose an efficient robust estimator, where the robust estimation equation is based on bounded scoring function and the covariate depended weight function. This method reduces the influence of outliers in response variables and covariates on parameter estimation, takes into account the correlation between data, and improves the efficiency of estimation. The simulation results show that the proposed method is robust and efficient.

Identifying Pathfinder Elements for Gold in Multi-Element Soil Geochemical Data from the Wa-Lawra Belt, Northwest Ghana: A Multivariate Statistical Approach

A multivariate statistical analysis was performed on multi-element soil geochemical data from the Koda Hill-Bulenga gold prospects in the Wa-Lawra gold belt, northwest Ghana. The objectives of the study were to define gold relationships with other trace elements to determine possible pathfinder elements for gold from the soil geochemical data. The study focused on seven elements, namely, Au, Fe, Pb, Mn, Ag, As and Cu. Factor analysis and hierarchical cluster analysis were performed on the analyzed samples. Factor analysis explained 79.093% of the total variance of the data through three factors. This had the gold factor being factor 3, having associations of copper, iron, lead and manganese and accounting for 20.903% of the total variance. From hierarchical clustering, gold was also observed to be clustering with lead, copper, arsenic and silver. There was further indication that, gold concentrations were lower than that of its associations. It can be inferred from the results that, the occurrence of gold and its associated elements can be linked to both primary dispersion from underlying rocks and secondary processes such as lateritization. This data shows that Fe and Mn strongly associated with gold, and alongside Pb, Ag, As and Cu, these elements can be used as pathfinders for gold in the area, with ferruginous zones as targets.

数据要素流通与安全的研究范畴与未来发展趋势

针对数据从信息技术时代的受控共享向数据技术时代的数据要素泛在流通演化的趋势,分析了数据共享与数据要素流通的差异,阐述了什么样的数据才能成为数据要素,提出了数据成为数据要素所必须具有的6个属性,定义了数据要素流通模型及主要环节,明确了数据要素流通的研究范畴,梳理了数据要素流通研究范畴的相关概念,厘清了研究范畴所涵盖的关键核心技术,并对未来需要突破的关键技术进行了展望。

信息资源管理学科视角下的数据要素研究

[目的/意义]数字经济背景下,信息资源管理学科需要进一步融入到数据要素化市场建设之中,积极建构新的学术增长点。[研究设计/方法]首先分析信息资源管理学科与数据要素的关联逻辑以及学科的角色建构问题,而后介绍信息资源管理学科视域下的若干核心议题,最后对两者融合的未来发展提出思考。[结论/发现]数据要素研究是信息资源管理学科的新领域和新方向,应充分发挥学科特色和优势,有组织地推进数据要素研究与实践。[创新/价值]从信息资源管理学科视域思考数据要素研究,为进一步扩大学科研究视野、拓展学科研究空间提供启示,为数据要素化与数字经济发展中的学科话语建构提供参考。

数据要素嵌入、双元创新与制造业转型升级

数据作为全新的生产要素成为制造业转型升级的重要引擎,双元创新是助推数据要素有效嵌入实体经济的关键动力。基于双元创新视角,剖析数据要素嵌入赋能制造业转型升级的理论机制,运用2008—2020年中国A股制造业上市企业数据进行实证检验。结果显示:数据要素嵌入能够有效赋能制造业转型升级,该结论在一系列稳健性检验后依然成立;双元创新在数据要素嵌入赋能制造业转型升级中发挥着中介作用,且更多地通过探索式创新促进制造业转型升级,利用式创新的中介效应尚不显著;进一步分析发现,数据要素嵌入赋能制造业转型升级的影响效应在企业内部微观特征和外部宏观环境层面存在异质性。因此,建议应有效推进数据要素市场化配置改革,营造数据要素赋能外部环境;持续提升企业探索式创新动力,激发数据要素赋能制造业转型升级的活力;积极引导企业数字化转型,推动数据要素与传统要素的深度融合。

Optimizing Data Collection Path in Sensor Networks with Mobile Elements

Exploiting mobile elements （MEs） to accomplish data collection in wireless sensor networks （WSNs） can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large data collection latency for the network, which is unacceptable for data-critical applications. In this paper, we address this problem by minimizing the traveling length of MEs. Our methods mainly consist of two steps： we first construct a virtual grid network and select the minimal stop point set （SPS） from it; then, we make optimal scheduling for the MEs based on the SPS in order to minimize their traveling length. Different implementations of genetic algorithm （GA） are used to solve the problem. Our methods are evaluated by extensive simulations. The results show that these methods can greatly reduce the traveling length of MEs, and decrease the data collection latency.

激活数据要素 赋能千行万业——《“数据要素×”三年行动计划(2024—2026年)》政策解读

[目的/意义]2024年1月,《“数据要素×”三年行动计划(2024—2026年)》正式印发。文章对其主要内容进行解读,旨在探讨政策制定的背后逻辑,明确政策的核心要义与具体导向,从而推动政策落实,加快数据要素市场化建设。[方法/过程]从乘数效应、保障支持、组织实施三大方面对政策主要内容进行阐释。[结果/结论]政策以各行业领域的实际需求为着眼点,以协同优化、复用增效、融合创新为数据要素乘数效应发挥的主要路径,同时保障数据要素流通的效率与安全,并最终通过多措并举来实现数据要素在各行业领域的深度融合和创新应用。

新质生产力与数字经济

新质生产力是以科技创新为主导、实现关键性颠覆性技术突破而产生的生产力,是摆脱了传统增长路径、符合高质量发展要求的生产力,是数字时代更具融合性、更体现新内涵的生产力。数字经济集信息技术、人工智能、大数据于一体,是推动经济增长的新引擎,也是当前发展新质生产力的重要抓手。数据作为新生产要素可以更好地赋能传统生产力改造升级,数字产业化与产业数字化为新质生产力形成提供实体基础,数字基础设施为新质生产力的形成提供坚实平台支撑。未来,结合数字经济特征和具体国情,要以数字经济高质量发展加快培育新质生产力,通过市场与政府有机结合协同提高数字创新能力、数实融合加快推进新兴产业与未来产业、培育创新型人才打造新型劳动者队伍。

数据要素在医疗健康领域的内涵、价值与应用

十七部门联合发布的《“数据要素×”三年行动计划(2024—2026年)》引发了社会的广泛关注。本文首先探讨医疗健康领域数据要素的本质、分类及其重要性。在此基础上,提出促进医疗健康数据融合创新的关键策略,包括通过技术赋能医疗健康数据的采集,推动医疗健康数据的整合与标准化工作,促进医疗健康数据的开放和共享,以及加强对医疗健康数据的安全保护。

政府数据开放到公共数据开放的嬗变

[目的/意义]分析政府数据开放到公共数据开放的嬗变有利于数据开放活动的健康发展,促进数据要素流通。[方法/过程]在梳理政府数据开放和公共数据开放两者关系基础上,从创新扩散理论出发分析嬗变的三维度表现及嬗变动力。[结果/结论]嬗变动力共有技术、组织和环境三个维度下的9个关键驱动因素,并提出了6个嬗变的趋势。

论数字经济推动新质生产力形成的路径

本文采用2013~2022年我国31个省(区、市)的面板数据,建立固定效应模型,从数据要素化、数字产业化、产业数字化、数字治理4个维度出发,实证检验了我国数字经济对新质生产力形成的影响及作用机制。研究发现,数字经济对新质生产力的形成有显著的正向影响,且在我国东部地区最为明显,中部地区次之,西部地区较为不明显。灰色关联度分析表明,战略性新兴产业和未来产业发展基础与我国新质生产力水平关联度最强。考察作用机制发现,数字产业化、产业数字化、数字治理是我国数字经济发展推动新质生产力形成的有效路径。大力发展数字化产业,促进数字技术创新;加快产业数字化转型升级,构建现代产业体系;提升数字治理能力,缩小新质生产力地区差距,成为推动我国新质生产力形成的重要政策启示。

数据“利益束”:数据权益制度新论

创设排他性、利己性的数据权利不利于海量数据的高效流通与多元价值的实现,加剧了数据私权化与效用化之间的内生性冲突。在权益区分保护理论框架下,采取数据利益保护进路更具正当性和相对优势。我国宜将数据利益作为数据权益制度的中心,建构人与人之间动态灵活、有机立体的利他性数据“利益束”范式,以有效协调和整合多元主体之间复杂的数据利益关系,并在数据“利益束”范式下,充分利用Web3.0以用户为中心的开放式价值互联网效能,通过点对点的数据利益流通来构建全网络利益格局。我国还应建立合理的激励与收益实现机制,促进所有数据主体共创和共享数据红利,在数据财产行为主义保护模式基础上,建立智能化治理体系来保障数据安全,最终形成中国自主且更能适应数字经济发展规律的新型数据权益制度体系,以此推进我国数字经济的健康发展。

数据要素与新质生产力:基于企业全要素生产率视角

新质生产力以全要素生产率提升为标志、核心是创新,数据要素对于提升创新水平与全要素生产率具有重要意义。本文将国家级大数据综合试验区试点作为一次准自然实验,基于我国2009—2021年制造业和服务业上市公司面板数据,利用双重差分模型识别数据要素影响企业全要素生产率的因果效应与作用机制。研究发现:数据要素显著提升了企业全要素生产率,且对服务业企业全要素生产率的影响大于制造业企业;经过一系列稳健性检验后上述结论依然成立。机制分析结果表明,数据要素主要通过数字化变革和创新对企业全要素生产率产生间接影响。调节效应表明,产业融合与数据要素会共同发挥作用、提升企业全要素生产率,且在中、高产业融合区域的作用效果没有显著差异,在低产业融合区域的效果不显著。

数据分类分级确权对数据要素价值实现的影响

数据确权是释放数据要素价值的基础,同时也是数据要素市场正常运行和不断发展的关键支撑。研究梳理了数据确权相关概念以及如何建立产权体系以实现数据确权的路径。在此基础上,本研究明晰了数据分类分级确权的具体方式,并基于价值链分析其对数据价值实现中各个环节的影响。研究结果表明,在数据采集环节数据分类分级确权制度能够激励数据供给,提高数据质量,同时激发市场活力;在数据组织环节,它细分了技术工作,保护隐私数据,并挖掘潜在价值;在数据流通环节,它能调节负外部性、降低交易成本、优化资源配置;最后,在数据利用环节,它在数据合规监管和数据价值再开发方面发挥了关键作用。

用户视角下的教育数据要素交易:安全感知与建议

教育数据要素作为推动教育变革的核心动力,正通过数据要素市场交易推动教育数字化转型纵深发展。然而,目前教育数据要素市场在数据确权、市场监督以及市场交易等制度层面存在不足,阻碍教育数据要素价值的释放。用户作为数据要素市场的核心参与者,其对教育数据要素交易的安全感知与建议是推进数据要素交易有序发展的重要因素。研究面向四类不同用户群体开展了定向调查,发现用户总体对教育数据要素交易持积极态度,且具有较为全面的安全感知,不同用户群体则在教育数据要素基本态度、安全感知与安全建议上存在差异。为加快教育数据要素交易市场建设,可以从加强教育数据要素市场保障,提高高等院校用户市场参与意愿,构建教育数据要素安全体系,满足不同用户群体的安全需求,塑造多元教育数据要素交易市场,推动交易机制向需求侧转型等方面改善。

“三权分置”路径下数据产权客体的类型谱系

“数据二十条”在表述数据产权“三权分置”时分别使用了“数据资源”“数据”“数据产品”三项表达来称谓“三权”的客体,从政策上肯认并确立了数据产权的客体对象。从法律视角审视,前述三项政策表达仍需经由学理阐释来论证其在法律上的定位及其相互关系,使之成为具有规范性的法律表达。“三权分置”路径下,“数据”的核心特征应包括信息属性、物理属性和集合属性,并在数据生产和流通使用的“价值链”上延展形成“数据资源”—“数据集合”—“数据产品”的类型层级。在分级分类构建原则下,作为产权客体的“数据”还可在横向上形成以公共数据与企业数据为一级子类型、公用/私用公共数据与公开/不公开企业数据为二级子类型的类型谱系。由此,便可在“三权分置”路径下阐明作为产权客体的数据的规范属性与类型谱系,为数据产权“三权分置”的法律化奠定基础和前提。