Scientific data is widely recognized as a strategic resource for research innovation and socioeconomic development. The progress of scientific research benefit from the openness of research resources including scientific data. The supporting role of scientific data for socioeconomic development in good alignment with national security concerns is increasing with the rapid development of trusted environments and tools to share data and IT services for the transition from information to knowledge. How to balance open data and security concerns is an urgent challenge for scientific data governance and services, among which, the construction and implementation of scientific data security standards is the core and outstanding weakness. This paper reviews the essential attribute of scientific data-An objective record of human scientific activities and discoveries, and the research achievements on new challenges and characteristics of scientific data security in recent years, especially in combination with the actual challenge of massive data loss to foreign countries in the current complex international situation. The authors propose the basic characteristics of scientific data security, including the data supply chain security in the global research ecology, the balance between data security and open data, traditional data security baseline threaten by the advanced new technology and the diversification of data sources, and the new security challenge on data fusion from multi-sources data. This paper definites scientific data security as the state of effective protection and compliant utilization of scientific data with the full protection of data security and privacy, social public interests, legitimate rights and so on. To meet the global trend of open science data and data security concerns, this paper proposes a basic framework of data security that covers the full life cycle dimension of scientific data and the security dimension which includes confidentiality, availability, integrity, traceability, controllability and non-repudiation, and the life cycle model conforms to the national "Measures for the Management of Scientific Data", which includes data collection, data storage, data processing, data transmission, data services and open sharing. This paper also puts forward a basic standard which is named general requirements for security management of scientific data, and this standard mainly specifies some requirements from the security dimension and the life cycle dimension, and the requirements include security management, life cycle security, and physical security of computer,storage media and its' environment, such as building, pickproof, waterproof and so on. In the classification standard for scientific data security, a three-dimensional classification of security, subject, and data stage is given, and the 4-level security model is determined based on the degree of damage to the affected objects of scientific data when the security attributes of scientific data are damaged, and in this standard open sharing of scientific data is clearly defined as an important level of 4-level security model. Finally, the article proposes some suggestions for scientific data security. In 2021, The UNESCO Recommendation on Open Science was released, which marks the official rise of the global Open science movement, and scientific data is one of the core knowledge resources. The research communities of China support the open sharing of scientific data to meet UNESCO Recommendation, and as practitioners of data centers actively participate in discussions and actions to ensure scientific data security and privacy through better data services or platforms with advanced technology. Scientific data security is a complex and comprehensive task that involves improper behavior by researchers or security challenges brought about by information technology, and these challenges require sufficient attention and further in-depth discussion.

In the process of constructing a knowledge graph for research and develop (R&D) projects, entity extraction for R&D project abstracts helps to quickly understand project content and promote the application and transformation of research results. This article adopts a scientific entity recognition model based on BERT-IDCNN-CRF (BERT combined with Iterative Dilated Convolutional Neural Network and Conditional Random Field) for the entity extraction task in the construction of knowledge graph for R&D projects. This model uses BERT to extract semantic representations from abstract texts, and then uses IDCNN to deeply capture local and global features in the text. Combined with CRF to learn the context transfer relationship between text labels. Finally it achieved the precision of 69.3%, the recall of 65.8%, and the F1-score of 67.5% in scientific entity recognition. On the basis of this model, this article proposes a knowledge graph construction scheme for R&D projects, and constructs a knowledge graph centered on R&D projects, which includes 12 kinds of entities and 13 kinds of relationships.

Scientific economic activities document the utilization of research funds, which form a critical component of scientific research. Detecting potential risk behaviors from scientific economic activities is crucial to risk management for research institutions. Most of the existing attempts, however, tackle the problem with traditional machine learning algorithms, which rely on the manual feature extraction. Undoubtedly, these methods cannot extract complex semantic features or fuse information from hybrid data for effective risk identification. To overcome these challenges, in this paper, we propose a novel Risk Identification model for Scientific Economic activities from HYbrid data (HY-RISE), which incorporates both textual and structured data. Firstly, we use a pretrained BERT module to capture the semantic information from textual data. After that, we introduce a BiGRU module to augment the contextual information in semantic embeddings. Finally, we use a shallow neural network to fuse the augmented semantic representation with other discrete features to obtain the final representation. Experimental results on the real reimbursement dataset demonstrate that HY-RISE apparently outperforms existing models in terms of effectiveness and robustness for risk identification.

科学数据是科研活动的成果,也是后续科研创新的基础.科学数据共享和流动能够有效实现其价值最大化.目前,我国科学数据已经取得很大进展,但仍需全面加强科学数据建设,实现科学数据的"强国梦".与此同时,科学数据安全问题也日益严峻,"边共享边保护"的实践遇到前所未有的挑战,急需全面加强科学数据安全的系统研究、标准体系及基础标准的研制和实施.

科研基础平台是国家科技创新的基础性、战略性平台。近10年来，我国科研基础平台在科学观测水平、制造工艺水平、数据获取水平、开放共享水平、科学管理水平、开发利用水平方面取得了跨越式发展，高水平支撑我国科技创新活动。展望未来，新的科研范式变革正在悄然到来，新兴科研信息化基础平台不仅支撑重大科技基础设施和野外台站朝着更大规模、更精确、更先进的方向发展，其本身还将对科研范式变革起到重要的推动作用，成为重大科技突破的“加速器”与“倍增器”，成为我国跻身创新型国家前列和迈进世界科技强国的关键支撑。

大数据技术在建设数字中国、发展数字经济过程中发挥着全局性、基础性的作用.经过近二十年的技术演进,大数据技术体系愈发庞大,新型软硬件系统层出不穷.本文对当前最主流、最具有引领性的大数据计算/存储等基础技术、大数据分析技术、大数据流通技术以及相关标准进行综述,并结合安防领域的特殊性,探讨具有安防特色的大数据技术方案.

[背景]运用大数据提升国家治理现代化水平是我国大数据战略和顶层设计的重要方向.中国科学院一直在实践以数据为驱动的一体化科研管理体系,探索现代化科研管理促进科技创新的应用模式.[方法]从2002年起,着手建设ARP(Academia Resource Planning,中国科学院资源规划)系统,历经四个五年计划的系统性推进,充分发挥了对管理创新的促进作用.[结果]在"十三五"期间,通过重构ARP系统,在业务驱动的基础上融合大数据分析技术,以数据驱动为理念,完成了新一代ARP全院应用,基本形成了覆盖全院主要管理业务场景的信息化应用生态.主要表现为:一是转变管理理念,在支持管理决策应用的基础上,全面覆盖一线科研人员,形成"服务→管理→决策"的服务型业务模式;二是简化业务流程,通过大数据治理发现业务流程的不合理之处,提升业务规范性;三是前后台业务分离,让各项业务处理微服务化,简化科研管理繁琐流程,提升服务效率;四是实现集约化管控和促进数据赋能,通过数据治理形成决策、管理、服务所需的数据资产,支持全局化共享应用.

科学数据是科研活动的重要成果,更是科技创新的数据资源基础.与此同时,科学数据安全问题也日益严峻,在数据共享实践过程中遇到了前所未有的挑战,需要全面加强科学数据安全标准规范体系的研究与制订.文章从信息安全属性、科学数据资源特征以及学科领域数据安全三个维度出发,深入分析了科学数据安全的特点与特征,提出了科学数据安全标准的五个重点研究方向,即科学数据安全框架、科学数据安全分级分类、科学数据权益保护、科学数据全生命周期安全以及领域科技资源安全.研究科学数据安全特征和标准体系,对于发挥科学数据驱动创新型国家建设的作用和促进《科学数据管理办法》的全面实施具有重要意义.

Abstract The concept of bionics combines biology and engineering technology to provide people with new principles, methods, and ways to improve and create new equipment, promote technological innovation, and solve technical problems in the most flexible, efficient, reliable, and economical way. Although information technology continues to develop, it still faces many challenges in the era of big data and intelligence. With the explosive growth of massive data, the demand of storage, calculation, and analysis, and its energy consumption and efficiency challenges, information technology is urgently needed to find a new development direction. Inspired by biotechnology, it is becoming an international frontier research direction to find information technology innovation scheme from biological structure. As active new research fields, DNA data storage and neural morphological computation as well as related research are representative directions, which have broad future development prospects. Based on the development status and trend of these two research directions, this study attempts to analyze the motivation, trend, and prospect of information technology development inspired by biotechnology. The next two decades will be an important time window for the cross integration of life field and information field. By learning and simulating from life system, and drawing on the new ideas, principles and theories provided by biotechnology research, the information field will produce a number of subversive technologies and applications, and it will affect the entire academic and industrial sessions.

作为国家科技创新的重要基础性战略资源,科学大数据日益对科研范式产生重要影响,世界各国对科学大数据的重视程度也达到前所未有的高度.目前,我国在科学大数据发展和应用方面已具备一定基础,拥有一批资源优势明显的科学数据中心和平台系统,但要真正盘活科学大数据资源,支撑大数据时代下多学科交叉融合和社会经济发展的创新模式,尚存在大数据处理技术亟待加强、数据开放共享不足、创新应用领域不深等突出问题.

区块链的安全监管技术已经成为区块链技术及应用研究的重要发展方向之一.本文从区块链的技术特点及其产生安全与监管问题的本源、区块链安全事件频发带来的监管技术发展以及区块链安全监管技术未来的主要研究方向三个方面进行了综述,重点阐述了区块链节点的追踪与可视化、公链的主动发现与探测、联盟链的穿透式监管和以链治链四个方向的技术研究进展情况.

[目的]为表明数据与计算平台在科学研究活动中的重要驱动作用,本文研究了数据、计算以及科学研究的发展与本质.[方法]本文简述了数据技术和计算技术的发展,通过拓扑材料计算、计算化学、引力波发现、黑洞成像和半监督学习图像识别等典型案例,表明了在各领域科研活动中,数据与计算平台极大地拓展了科学研究的深度和广度,为当代科学研究提供了新的手段与方法.[结果]本文认为摩尔定律的驱动、大数据爆炸式的增长以及人工智能的再次蓬勃发展,都和数据与计算技术的发展呈现密不可分的关系.[结论]以大数据、人工智能技术为代表的数据与计算平台将作为科学研究一种独立、不可或缺的投入要素,融入科学研究活动的全过程,数据与计算平台将成为世界各国驱动现代科学研究发展的重要基础设施.

科研信息化基础环境是在科研信息化劳动工具中,满足共享需求、提供共享服务、支撑科研活动的软硬件系统和信息化环境.它涵盖了以硬件设施为主的“硬”服务环境、以软件和数据为主的“软”服务环境,以及包括协同工作环境、运维平台在内的运行管理和服务环境.文章简要综述了国外科研信息化基础环境建设的最新进展,阐述了我国国家科研信息化基础环境的发展现状,通过近年来中科院在科研信息化基础环境建设中的实践与经验,分析了我国国家科研信息化基础环境建设中的不足,并针对问题提出了关于我国国家科研信息化基础环境发展的建议.

The article firstly overviewed Big Data Research and Development Initiative announced recently by the U.S. federal government from a perspective of big data-based information network security development, especially analyzed the positioning , objective and expected results of XDATA program. Subsequently, the article provided in-depth analysis of the features at different levels for U.S. information security strategy in the era of big data. As a conclusion, the article indicates that big data has become a cross-cutting area across national strategies for innovation, security, ICT industry development and information security, and U.S. has created a virtual information network security strategy on the basis of big data which aimed at addressing the core technical challenge and strengthening the predominance of information security strategy as whole in future.

This article describes the development trend of domestic and international information security, by focusing on the security status and the main problems of the research informationization. Technologies and security countermeasures are proposed and discussed.

A new fully automatic sounding system of middle atmosphere which succeeded in employ-ing GPS positioning of 1680 MHz telemetry system has been introduced.Composed of balloon-borne sensors as well as ground tracking and signal processing equipments,the system has replaced the original radar or theodolite with GPS to track the radiosonde with no limitation of low elevation angle.Meanwhile,wide lobe antenna and low-noise receiver have been utilized to avoid losing the target.With this sounding system,the atmospheric electric field sounding experiments were con-ducted and satisfactory results have been obtained.Attributing to its portability,easy operation,low cost and favorable maneuverability and reliability,this sounding system is quite prospective for application in the near space environment detection,middle atmosphere scientific experiments and conventional meteorologic sounding as well.

介绍空间科学探测活动的特点与标准化工作情况,提出我国在空间科学探测领域实施标准化工作的思路和顶层构架。

一 会议的背景和基本情况 世界空间科学大会是国际上空间科学界规模最大、最为重要的学术会议,由国际空间研究委员会(Committee on Space Research,COSPAR)每两年举办一次,至今已经举办了36届.中国北京作为承办国和承办城市,在世界空间科学大会历史上是第一次.

通过对科研项目评估方法的系统研究,对空间科学和空间科学工程项目的内在特性进行了分析,对定性与定量结合的评估方法应用进行了分析,应用层次分析法对空间科学工程项目立项建立了5个一级评估指标,13个二级评估指标、41个三级评估指标体系,判断矩阵和模型,并应用实例进行了检验.

科研项目管理通常指通过协调与科研项目(或项目计划)相关的各种关系,有效利用人、财、物等科技资源,以促进项目目标实现的动态活动.科研项目管理按时间分为立项管理、实施管理以及结题验收管理;按管理方式分为目标管理和过程管理.科研项目管理研究的内容非常广泛,涉及到科技计划体系、项目立项评审管理、项目投入与产出关系,以及项目管理办法、过程评估、验收、经费使用等诸多方面.在这些研究内容中,关于科研人员在研项目数量与经费、科研时间与兼职、科研人员年龄与争取经费能力等关系的研究,主要是从定性角度进行分析和描述.本文利用抽样调查资料,对科研项目管理中存在的这些关系进行定量研究,试图与定性分析相互结合.