研究数据基础设施在研究范式演变中的新作用

IF 1.5 3区 管理学 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE Journal of Data and Information Science Pub Date : 2024-03-05 DOI:10.2478/jdis-2024-0011
Yizhan Li, Lu Dong, Xiaoxiao Fan, Ren Wei, Shijie Guo, Wenzhen Ma, Zexia Li
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引用次数: 0

摘要

研究数据基础设施是网络和物理空间的基石,推动着数据密集型科学研究模式的发展。本意见书概述了全球研究数据基础设施,从与研究数据基础设施相关的国家路线图和战略文件中汲取了深刻见解。它强调了研究数据基础设施的关键作用,提出了四项新使命,旨在将研究数据基础设施定位为当前科学研究与交流生态系统的核心。研究数据基础设施的四项新使命是(1) 作为先锋,超越学科边界,以问题和数据为导向的洞察力应对复杂、前沿的科学和社会挑战;(2) 作为架构师,建立数字化、智能化、灵活的研究和知识服务环境;(3) 作为平台,促进高端学术交流;(4) 作为协调者,平衡科学开放与伦理需求。
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New roles of research data infrastructure in research paradigm evolution
Research data infrastructures form the cornerstone in both cyber and physical spaces, driving the progression of the data-intensive scientific research paradigm. This opinion paper presents an overview of global research data infrastructure, drawing insights from national roadmaps and strategic documents related to research data infrastructure. It emphasizes the pivotal role of research data infrastructures by delineating four new missions aimed at positioning them at the core of the current scientific research and communication ecosystem. The four new missions of research data infrastructures are: (1) as a pioneer, to transcend the disciplinary border and address complex, cutting-edge scientific and social challenges with problem- and data-oriented insights; (2) as an architect, to establish a digital, intelligent, flexible research and knowledge services environment; (3) as a platform, to foster the high-end academic communication; (4) as a coordinator, to balance scientific openness with ethics needs.
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来源期刊
Journal of Data and Information Science
Journal of Data and Information Science INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.50
自引率
6.70%
发文量
495
期刊介绍: JDIS devotes itself to the study and application of the theories, methods, techniques, services, infrastructural facilities using big data to support knowledge discovery for decision & policy making. The basic emphasis is big data-based, analytics centered, knowledge discovery driven, and decision making supporting. The special effort is on the knowledge discovery to detect and predict structures, trends, behaviors, relations, evolutions and disruptions in research, innovation, business, politics, security, media and communications, and social development, where the big data may include metadata or full content data, text or non-textural data, structured or non-structural data, domain specific or cross-domain data, and dynamic or interactive data. The main areas of interest are: (1) New theories, methods, and techniques of big data based data mining, knowledge discovery, and informatics, including but not limited to scientometrics, communication analysis, social network analysis, tech & industry analysis, competitive intelligence, knowledge mapping, evidence based policy analysis, and predictive analysis. (2) New methods, architectures, and facilities to develop or improve knowledge infrastructure capable to support knowledge organization and sophisticated analytics, including but not limited to ontology construction, knowledge organization, semantic linked data, knowledge integration and fusion, semantic retrieval, domain specific knowledge infrastructure, and semantic sciences. (3) New mechanisms, methods, and tools to embed knowledge analytics and knowledge discovery into actual operation, service, or managerial processes, including but not limited to knowledge assisted scientific discovery, data mining driven intelligent workflows in learning, communications, and management. Specific topic areas may include: Knowledge organization Knowledge discovery and data mining Knowledge integration and fusion Semantic Web metrics Scientometrics Analytic and diagnostic informetrics Competitive intelligence Predictive analysis Social network analysis and metrics Semantic and interactively analytic retrieval Evidence-based policy analysis Intelligent knowledge production Knowledge-driven workflow management and decision-making Knowledge-driven collaboration and its management Domain knowledge infrastructure with knowledge fusion and analytics Development of data and information services
期刊最新文献
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