一、引言
标准在国民经济和社会发展中担任重要的角色。在宏观层面，标准对社会经济发展全局起到重要作用，是国家基础性制度的重要组成部分，是可持续发展的重要保障。同样，当前“得标准者得天下”，标准影响市场的控制权。因而，通过标准与技术的融合，实现技术标准化、标准垄断化，可以最大限度地获取市场份额。在微观层面，标准作为重要技术创新成果的汇集，其事关企业的生存和发展，是企业组织生产和经营的依据，高标准将助力企业高质量发展。
为了适配数字经济发展，发挥标准化的引领作用需要其进行数字化转变。标准在数字经济时代将有效推动企业和行业之间的质量信息协调，是促进生产商、供应商、销售商、消费者甚至包括竞争对手在内的全产业链生态配合的必要基石。在推动数字经济发展过程中，高质量数字化标准有效实施是提升质量基础设施能力、串联改造产业价值链的核心要素，也将促进标准与数字化转型的生产应用紧密结合。数字化将会进一步助推标准化的发展。利用数字化技术对标准化工作和标准本身赋能，创建标准结构和内容的新形式，实现灵活、高效、交互的标准实施过程，推动标准管理体系与管理能力智能化。
二、标准数字化发展历程
国际上具有影响力的标准化机构为实现多国标准互换性和标准通用性，制定标准数字化转型相关战略。2017年，ISO副秘书长在“标准与数字化：拥抱变革”的报告中提出数字化影响下的未来标准化；2018年，ISO通过技术管理委员会94号决议，建立了机器可读标准的战略咨询小组，提出了机器可读标准（SMART）概念，发布了实施路线图；2021年，ISO发布《ISO战略2030》，认为数字技术是ISO变革的驱动因素之一。IEC作为世界上成立最早的国际性电工标准化机构，2017年在发展规划中提出IEC将继续为其核心业务的根本性改变做准备，其中包括可直接由机器使用的新型数字标准。
2020年IEC SMB重启SG12“数字化转型和系统方案”战略组，其工作范围包括数字化转型有关内容、国际标准的数字化转型方法等。2021年IEC CB成立“SMART标准化与合格评定”任务组。各国为提高国家产品和技术的国际市场占有率和国际竞争力，出台多项标准数字化转型政策。美国航空航天工业协会于2005年提出未来标准将作为一系列数据单元进行管理和控制；2021年，ANSI正式发布《美国标准战略》，提出数字化工具可以有效地用于优化全球标准的制定。俄罗斯于2019年在《2019—2027年俄罗斯标准化发展措施方案》提出将国家标准转换为“机器可读格式”。德国DIN/DKE为支持企业数字化转型于2017年将“未来机器可执行标准的结构和格式”作为其重点领域。英国BSI于2019年启动在数字化环境中进行标准协作开发的敏捷流程。
我国为标准数字化转型进行一系列行动。2009年，中国航空领域相关机构将标准处理、存储为数据单元形式，并与工业软件、操作系统等结合，使得标准使用形式能够基本满足标准使用需求。2021年10月我国发布《国家标准化发展纲要》，其为我国标准化事业的发展提供了可遵循的纲领性文件，其中对标准数字化给出了明确的方向：“推动标准化工作向数字化、网络化、智能化转型”。2022年，筹建全国标准数字化工作组，负责标准数字化基础通用、建模与实现共性技术、应用技术等领域国家标准制修订工作。
三、工业生产标准数字化转型的路径
当前，工业生产均在进行数字化转型，但是标准使用与其适配性存在问题。工程技术人员获取标准严重依赖专业经验和标准使用背景，因此在选用标准时易出现误区。同时，传统标准无法与工业生产数字化升级协调统一，因而无法实时掌握贯标效果，难以即时发现标准制修订中的指标不完善、不齐全等问题。
国家工信部发布《原材料工业两化深度融合推进计划（2015-2018年）》，“以公共平台建设、智慧工厂示范、技术推广普及为着力点，努力实现流程工业全链条全系统智能化”。伴随着新技术手段不断涌现及应用水平不断提升，高新数字化技术在工业生产领域开始覆盖全产业链，进而促进实时洞察各方需求与定制化生产新模式有机结合。正在进行数字化转型的工业生产领域，最终目标是将人的知识经验通过系统进行固化，减少人的干预，直至实现无人干预的目标。
在生产经营全流程中，通过数字化技术实现最优生产，系统会自动进行生产优化组合，选择最优化的方案执行。在此过程中无法离开标准的规范化作用，然而目前标准普遍处于纸质或PDF版，在标准选择阶段，需通过具有一定专业背景及相关储备的标准使用者经过对标准内容比对和分析，选择适合应用场景的标准进行使用。在标准使用阶段，传统标准的使用只能依靠人工输入的方式与数字化转型的产业链进行联通。
随应用环境复杂程度提升，标准使用过程的效率相应降低。根据ISO/IEC提出的SMART标准数字化路径，实现工业生产应用中标准数字化转型主要分为机器可识别标准、机器可执行标准和机器可决策标准三个阶段。
第一个阶段需实现将传统标准文本转化为机器可识别的文档类型，为接下来进行标准的数字化技术处理奠定基础。目前，对于标准文本的转化分为如下几步：（1）基于PDF文本进行处理，通过OCR技术，利用文档中的暗亮，确定其形状；（2）利用字符识别方法将形状翻译成计算机文字；（3）通过文字软件，结合上下文对最终矢量化文档进行编辑加工。
第二个阶段重点为可根据应用场景选择性地访问附有语义的标准内容，主要实现按照需求获取标准内容。国家标准、行业标准、团体标准等各级标准之间存在技术要求的差异。同时，各领域标准目前已形成体系，各标准范围之间存在关联，标准内容本身也存在联系。在该阶段，需将机器可处理的文档进行数字化加工，赋予其语义，选择最贴合应用环境的知识颗粒度进行标准离散化处理，深度挖掘内容中的相互关联性和系统性，使标准不再以文档的形式独立存在，而是将标准所包含的知识点形成一个属于该领域的知识网络，一个属于该领域标准的“知识大脑”。根据需求输入，经知识网络的分析和匹配，输出与之相关的标准内容，使得标准的内容更具有灵活性和实用性。在该阶段，首先结合具体应用场景对标准中的关键元素进行比对分析，对重要指标内容的限定类和限定项进行总结归纳，获得对接应用场景的基础模型。基于此，对标准信息的实体、实体关系以及属性进行抽取，通过对实体的链接和重复项的合并进行标准知识图谱的融合。最后，借助对标准知识的推理和知识图谱质量评估进行标准知识图谱的加工以及优化。基于标准知识图谱，根据具体应用场景进行智能对接，实现智能问答、适用标准推送等一系列标准服务。
最后一个阶段，机器能够以更为复杂的方式执行或解析与标准相关内容。前两阶段主要基于现有标准，进行标准的数字化，而该阶段覆盖面已不局限于现有标准内容，而是基于大数据等数字化智能化技术，实现标准数字化执行与数字化标准的形成。关联服务于生产现场管控的物联网平台，通过IOT协议、智能传感技术和无线网络通讯协议等技术，对生产现场的设备运行数据、巡检作业数据、安全环保数据、物流数据等进行全面采集。同时，面向企业提供的生产运行综合管理平台，通过对生产过程数据、实时数据、化验分析、计量等生产数据的集成，实现对生产执行、调度、运行等业务领域全覆盖，达到生产信息集成、业务管理协同。
综合采集上层和下层的数据，实现获取不中断的数据流，并通过自学习的方式改善内容处理及访问方式，使用方可通过自动问答或智能推送获取目标标准内容。
标准数字化不仅是标准存在 形式的“数 字化”，还包括标准化的数字化，后者主要是利用数字化技术推动标准化工作的生命周期全过程的发展，更好地实现标准的“管、查、用、编”。如果在生产过程中出现标准的缺失，将在数据链条中得到即时的反馈。同时，随着技术、设备等的发展，标准的技术指标也需进行修订，结合各标准的执行情况和反馈，标准的适配情况也将得到即时预警。基于现有标准知识覆盖及使用情况进行信息收集，依据实际情况进行标准的制修订，以开源的方式进行标准的编写，实现快速迭代和动态更新。针对已形成的标准，工厂可比对已有标准技术指标等相关数据，通过边缘计算技术实现前端状态监控、诊断分析和预警报警等功能，为实现生产现场智能化设备监控维护、生产操作管控、安全环保管控等提供数据支持，促进业务模式提升和变革，为智能生产建设奠定基础。
四、标准数字化关键技术
1、光学字符识别技术
字符作为标准中占比最大的形式，是实现传统标准向机器可识别标准转型的关键。进行字符的识别需先进行字符特征的机器学习，基于识别系统储备的相关字符信息，可针对输入字符的明暗特征等信息进行储备知识的调用，得到字符的识别结果。当前识别方法分为统计特征字符识别技术、结构字符识别技术和基于神经网络的识别技术。在识别字符后，根据原排版的格式进行版面恢复。最后根据特定的语言上下文关系，对识别结果进行校正。标准的结构和起草规则严格按照GB/T 1.1《标准化工作导则 第1部分：标准化文件的结构和起草规则》进行编写，与光学字符识别技术结合使用，对识别结果的准确性有一定程度的推动作用。
2、知识图谱
传统标准知识数据库常以传统关系性数据库为基础，冗余性高，分布分散，关联性较弱，较少从语义层面挖掘知识的关联性，其与成体系且具有高关联性的标准知识本身相矛盾。为打破标准知识的“孤岛”，借助知识图谱将其关联。构建标准知识图谱首先需要获取数据，它们可以以表格、文本等不同结构化程度的知识为来源，对实体识别、关系和属性进行抽取后，需要对数据进行知识融合，解决来源不同导致的数据交叉、重叠等问题，将来源不同的知识融合成一个知识集合体。为实现结构化、网络化的知识体系，还需进行本体构建、知识推理和质量评估，以此保障最终标准知识库的质量。
3、自然语言处理
标准存在初期是以人为使用对象，为实现从人使用到机器使用的跨越，需要搭建人与计算机之间用自然语言进行有效通信的理论和方法。自然语言处理本质上是基于词典，通过词频统计，上下文语义分析等方式方法进行语料分词。在标准文本领域中的自然语言处理就是将完整的标准碎片化为最小词性且富含语义的词项单元。面对大量标准，一般情况需借助机器学习对其进行处理，除了借助人工标注的传统机器学习方法还可借助深度学习模型，进而实现不同层次特征的自然语言处理。针对不同的应用场景和专业背景，标准的自然语言处理存在一定的差异性，充分融合领域知识以及专业概念，对关键信息进行分解、标注和重组尤为重要。在进行模型训练的过程中，需将算法的准确度置于合理区间。在标准数字化过程中，标准文本的自然语言处理贯穿全过程，需紧密结合其应用场景和专业领域，以此获得合适的模型。
五、结语
标准数字化已成为适应全球数字经济发展下工业生产发展的重要组成部分。我国大部分标准仍处于纸质标准或PDF版，与基本实现机器可识别标准的ISO、IEC等标准化机构存在距离，各领域开始聚焦标准本身，结合应用场景，进行标准数字化转型，构建覆盖标准“管、查、用、编”全生命周期的数字生态系统，为我国数字经济发展保驾护航。标准数字化在未来的发展中存在如下四方面的挑战：
第一，在技术层面，标准数字化涉及一系列当下最先进的技术，包括数字化加工、自然语言处理，知识图谱构建技术等，如何攻破各项技术在标准数字化方面的应用是转型的关键；
第二，在数据层面，标准数字化涉及国家标准、行业标准、团体标准、企业标准以及企业内部的技术规范书等文件，存量数据多，由于标准数字化对离散化程度要求高，加工难度大，需根据重要程度进行差异化加工标引，打好数据基础从而保证将来的应用；
第三，在业务层面，标准数字化建设最终是服务于各公司的工业生产需求，因此在建设过程中应有相关业务专家参与，分析并获得最适宜的标准知识颗粒度，推动标准及其应用场景的智能对接；
第四，在标准化工作的管理方面，数字化技术将推动标准的全周期更为高效、便捷，随着线上、开源等多种方式的出现，标准化的管理体制还需要进行调整，且与国家标准、行业标准、团体标准等各级标准相关的制度应根据实际情况和标准本身的特点进行差异化制定。
翻译
Introduction.
Standards play an important role in national economic and social development. At the macro level, standards play an important role in overall social and economic development. They are an important part of a country’s basic system and an important guarantee for sustainable development. In the same way, the current “standards win the world”, standards influence the control of the market. Therefore, through the integration of standards and technologies, technology standardization and standard monopoly can be realized to obtain the maximum market share. At the micro level, as the collection of important technological innovation results, standards are related to the survival and development of enterprises, and are the basis for enterprises to organize production and management. High standards will help enterprises develop with high quality
In order to adapt to the development of digital economy, the leading role of standardization needs its digital transformation. In the era of digital economy, standards will effectively promote the coordination of quality information between enterprises and industries, and are the necessary cornerstone to promote the ecological coordination of the whole industrial chain including producers, suppliers, sellers, consumers and even competitors.
In the process of promoting the development of digital economy, the effective implementation of high quality digital standards is the core factor of improving the quality infrastructure capacity and connecting the industrial value chain, and it will also promote the close integration of standards and the production and application of digital transformation. Digitization will further boost the development of standardization. The digital technology is used to empower the standardization work and the standard itself, create a new form of the standard structure and content, realize the flexible, efficient and interactive standard implementation process, and promote the intelligent standard management system and management ability.
Development process of standard digitization.
Influential standardization institutions in the world develop strategies.
In order to realize the interchangeability and universality of standards in many countries, influential standardization institutions in the world develop strategies related to the digital transformation of standards. In 2017, the ISO Deputy Secretary General proposed the future of standardization under the influence of digitalization in his report “Standards and Digitalization: Embracing Change”; In 2018, ISO adopted Resolution 94 of the Technical Management Committee to establish a strategic advisory group on machine-readable standards, put forward the concept of Machine-readable standards (SMART), and issued a roadmap for implementation. In 2021, ISO released the ISO Strategy 2030, which identified digital technology as one of the drivers of ISO change. As the world’s oldest international electrical standardization body, IEC continues to prepare for fundamental changes in its core business, including new digital standards that can be used directly by machines, according to its 2017 development plan.
In 2021, IEC CB set up the task force of “SMART Standardization and Conformity Assessment.
In 2020, IEC SMB restarted SG12 “Digital Transformation and Systems Solutions” strategy group, whose scope of work includes digital transformation related content, international standard digital transformation methods, etc. In 2021, IEC CB set up the task force of “SMART Standardization and Conformity Assessment”. In order to improve the international market share and competitiveness of national products and technologies, various countries have introduced a number of standard digital transformation policies.
The Aerospace Industries Association proposed in 2005 that future standards would be managed and controlled as a series of data units; In 2021, ANSI formally released the American Standards Strategy, which proposes that digital tools can be used effectively to optimize global standards development. In 2019, Russia proposed the conversion of national standards to a “machine-readable format” in the Measures for the Development of Standardization in Russia for the period 2019-2027. DIN/DKE, in order to support the enterprise digital transformation, has made “the structure and format of future machine executable standards” its focus area in 2017. BSI launched an agile process for standard collaborative development in a digital environment in 2019.
Our country carries out a series of actions for digital transformation of standards.
In 2009, relevant institutions in the aviation field of China processed and stored the standards in the form of data units, and combined them with industrial software and operating systems, so that the use form of the standards can basically meet the use requirements of the standards. In October 2021, China issued the “National Standardization Development Program”, which provides a programed document for the development of the standardization cause and gives a clear direction for the digitization of standards: “Promote the standardization work to digital, network, intelligent transformation”. In 2022, a national standards digitization working group will be prepared to take charge of the revision of national standards in the fields of basic generalization of standards digitization, modeling and realization of generic technology and application technology.
Third, the path of digital transformation of industrial production standards.
There are some problems in the use of standards and their suitability.
At present, industrial production is undergoing digital transformation, but there are some problems in the use of standards and their suitability. The acquisition of standards by engineering and technical personnel depends heavily on professional experience and standard application background, so it is easy to have errors in the selection of standards. At the same time, the traditional standards cannot be coordinated and unified with the digital upgrading of industrial production, so it is impossible to grasp the effect of standard implementation in real time, and it is difficult to find the problems of imperfect and incomplete indicators in the revision of the standard system.
The Ministry of Industry and Information Technology of the People’s Republic of China issued the Deep Integration of the Raw Material Industry and the Raw Material Industry (2015-2018), “focusing on the construction of public platforms, smart factory demonstration and technology popularization, and striving to realize the intellectualization of the whole process industry chain and the whole system”. With the continuous emergence of new technological means and the continuous improvement of application level, high-tech digital technology begins to cover the whole industrial chain in the field of industrial production, thus promoting the organic combination of real-time insight into the needs of various parties and the new mode of customized production. In the field of industrial production undergoing digital transformation, the ultimate goal is to solidify human knowledge and experience through the system and reduce human intervention until no human intervention is achieved.
The optimal production is realized through digital technology.
In the whole process of production and management, the optimal production is realized through digital technology, and the system will automatically optimize the production combination and select the optimal plan for implementation. In this process, the standardization function of the standard cannot be left. However, currently the standard is generally in paper or PDF version. In the stage of standard selection, the standard users with certain professional background and relevant reserves should select the standard suitable for application scenarios after comparing and analyzing the content of the standard. At the stage of standard use, the use of traditional standards can only rely on manual input to connect with the industrial chain of digital transformation.
As the complexity of the application environment increases, the efficiency of the standard use process decreases correspondingly. According to the digital path of SMART standard proposed by ISO/IEC, the digital transformation of standards in industrial production application can be divided into three stages: machine identifiable standard, machine executable standard and machine decision standard.
The first stages.
The first stage is to transform the traditional standard text into a machine-recognized document type, which lays the foundation for the digital processing of the standard technology. At present, the conversion of standard text is divided into the following steps: (1) Processing based on PDF text, through OCR technology, using the dark and light in the document to determine its shape; (2) Using character recognition method to translate shapes into computer characters; (3) Edit and process the final vectorized document with text software and context.
The second stage.
There are differences in technical requirements among national standards, industry standards and group standards.
The second stage focuses on the selective access to the standard content with semantics according to the application scenario, and the main realization is to obtain the standard content according to the demand. There are differences in technical requirements among national standards, industry standards and group standards. At the same time, the standards in various fields have formed a system, there is a correlation between the scope of each standard, the content of the standard itself is also linked.
At this stage, documents that can be processed by machines should be digitized, given their semantics, and the knowledge granularity that best fits the application environment should be selected for standard discretization processing. The interrelation and systematicness in the content should be deeply explored, so that the standard no longer exists independently in the form of documents, but the knowledge points contained in the standard should be formed into a knowledge network belonging to this field.
A “knowledge brain” that is standard in the field.
According to the requirements of input, through the analysis and matching of knowledge network. Output related to the standard content, making the content of the standard more flexible and practical. At this stage, the key elements of the standard are compared and analyzed in combination with specific application scenarios. And the qualified categories and items of important indicators are summarized and concluded. So as to obtain the basic model for docking application scenarios.
Based on this, the entity, entity relationship and attribute of standard information are extracted. And the fusion of standard knowledge graph is carried out by merging entity links and duplicate items. Finally, by means of reasoning of standard knowledge and quality assessment of knowledge graph, processing and optimization of standard knowledge graph are carried out. Based on the standard knowledge graph, intelligent docking is carried out. According to the specific application scenarios, and a series of standard services. Such as intelligent question and answer and applicable standard push are realized.
The final stage.
In the final stage, the machine is able to execute or parse standards-related content in a more complex manner. The first two stages are mainly based on existing standards for the digitization of standards. And the coverage of this stage is no longer limited to the content of existing standards. But based on big data and other digital intelligent technologies, to realize the digitalization of standards and the formation of digital standards.
Associated with the Internet of Things platform serving the management and control of the production site. The equipment operation data, inspection operation data, safety and environmental protection data, logistics data and other data of the production site are comprehensively collected through IOT protocol, intelligent sensing technology and wireless network communication protocol. At the same time, the integrated management platform of production operation provided for enterprises can fully cover the business fields of production execution, scheduling and operation. It was by integrating production process data, real-time data, laboratory analysis, measurement. And other production data, and achieve the integration of production information and cooperation of business management.
Users can obtain the target standard content through automatic question-and-answer or intelligent push.
Comprehensive collection of upper-layer and lower-layer data to achieve uninterrupted data flow and improve content processing and access through self-learning. Users can obtain the target standard content through automatic question-and-answer or intelligent push.
Standard digitization is not only the “digitalization” of the existence form of standards. But also the digitalization of standardization. Which mainly uses digital technology to promote the development of the whole process of the life cycle of standardization and better realize the “management, investigation, application and compilation” of standards. If there is a missing standard in the production process, there is immediate feedback in the data chain. At the same time, with the development of technology and equipment, the technical indicators of the standard also need to be revised. Combined with the implementation and feedback of each standard, the adaptation of the standard will also get instant warning.
Collect information based on the knowledge coverage and use of existing standards. Revise the standards according to the actual situation, compile the standards in an open source way. And realize rapid iteration and dynamic update. In view of the established standards, the factory can realize front-end status monitoring, diagnosis and analysis, early warning and alarm. It was by comparing the relevant data of the existing standard technical indicators. Through edge computing technology, providing data support for the realization of monitoring and maintenance of intelligent equipment in the production site, production operation control, safety and environmental protection control, etc., promoting the improvement and reform of the business model, and laying the foundation for the construction of intelligent production.
Key technologies of standard digitization.
Optical character recognition technology.
As the most important form of standard, character is the key to realize the transformation from traditional standard to machine recognizable standard. Character recognition requires the machine learning of character features. Based on the relevant character information stored by the recognition system. The reserve knowledge can be called. For the light and dark features of input characters and other information to obtain the character recognition results.
The current recognition methods include statistical character recognition, structural character recognition and neural network based recognition. After the characters are identified, the layout is restored according to the original typesetting format. Finally, according to the specific language context, the identification results are corrected. The structure and drafting rules of the standard are written in strict accordance with GB/T 1.1 “Standardization Work Guidelines Part 1. Structure and Drafting Rules of Standardized Documents”. The combination with optical character recognition technology promotes the accuracy of the recognition results to a certain extent.
Knowledge Map.
The traditional standard knowledge database is usually based on the traditional relational database. With high redundancy, scattered distribution and weak relevance. It seldom mines the relevance of knowledge from the semantic level. Which is contradictory with the systematic and highly relevant standard knowledge itself. In order to break the “island” of standard knowledge, it is related by knowledge graph. The construction of standard knowledge map requires data acquisition first. Which can be derived from knowledge of different structural degrees such as tables and texts.
After entity identification, relationships and attributes are extracted, knowledge fusion of data is required to solve problems. Such as data crossover and overlap caused by different sources. And knowledge from different sources is integrated into a knowledge set. In order to realize a structured and networked knowledge system. Ontology construction, knowledge reasoning and quality evaluation are needed to ensure the quality of the final standard knowledge base.
Natural Language processing.
In the early stage of its existence, standards are used by human beings. In order to realize the leap from human beings to machines, it is necessary to establish the theory. And method of effective communication between human beings and computers with natural language. In essence, natural language processing is based on dictionaries. And word segmentation is carried out by means of word frequency statistics, contextual semantic analysis and other methods. In the field of standard text, natural language processing is the fragmentation of complete standards into lexical units. With minimal parts of speech and rich semantics.
In the face of a large number of standards, they generally need to be processed by machine learning. In addition to the traditional machine learning method of manual annotation, deep learning models can also be used to realize natural language processing with different levels of features. According to different application scenarios and professional backgrounds, standard natural language processing has certain differences. It is particularly important to fully integrate domain knowledge and professional concepts, and decompose, label and reorganize key information. In the process of model training, the accuracy of the algorithm should be placed in a reasonable range. In the process of standard digitization, the natural language processing of standard text runs through the whole process. Which needs to be closely combined with its application scenarios and professional fields, so as to obtain a suitable model.
Conclusion.
Standard digitization has become an important part of industrial production under the development of global digital economy. Most of our standards are still in paper standards or PDF versions, and there is a distance between them and ISO. IEC and other standardization institutions that basically realize machine-recognizable standards. All fields begin to focus on the standards themselves, combine application scenarios, carry out digital transformation of the standards. And build a digital ecosystem that covers the whole life cycle of “management, investigation, use and compilation” of the standards. Escort the digital economy development of our country.
There are four challenges in the future development of standard digitization.
First, at the technical level, standard digitization involves a series of the most advanced technologies. Including digital processing, natural language processing, knowledge graph construction technology, etc. How to break through the application of various technologies in standard digitization is the key to the transformation.
Second, at the data level, standard digitization involves documents. Such as national standards, industry standards, group standards, enterprise standards and internal technical specifications of enterprises. There are a lot of stock data. Since standard digitization requires high degree of discretization and is difficult to process. Differentiated processing and indexing should be carried out according to the degree of importance to lay a good data foundation so as to ensure future application.
Thirdly, at the business level, the digital construction of standards ultimately serves the industrial production needs of various companies. Therefore, relevant business experts should participate in the construction process to analyze and obtain the most appropriate granularity of standard knowledge. And promote the intelligent docking of standards and their application scenarios.
Fourthly, in the management of standardization, digital technology will promote the whole cycle of standards to be more efficient and convenient. With the emergence of online, open source and other ways, standardized management system still needs to be adjusted. And the system related to national standards, industry standards, group standards and other standards should be differentiated according to the actual situation and the characteristics of the standard itself.
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