数据中台在科技情报中的应用

Application of Data Central-Platform in Scientific and Technological Intelligence

随着数据资源的不断积累与信息化建设的不断推进,在传统烟囱式IT建设方式下,科技情报机构独立采购或自建的各种信息系统,在内部形成诸多数据孤岛;而在互联网、移动互联背景下,各种APP、服务号、小程序、O2O平台等新模式下产生的外部数据与传统系统的内部数据无法互通,这进一步加剧了数据孤岛问题。系统的多样性、多态性,数据的多源性、异构性增加了IT架构的复杂度。为解决系统平台底层数据打通与适应快速部署应用的需求,科技情报领域开始重视数据中台的建设与应用。大数据的兴起与人工智能的新发展,给向来重视数据基础以及情报与智能密切关系的情报学带来了新的机遇与挑战,并于最近10年来形成了一些新的模式,渐渐成为情报学的主流,典型的有:基于事实型数据的工程化情报、计算型情报、快速响应情报以及情报3.0。这些情报理论研究的探索为数据中台在科技情报中的应用提供了理论基础。在这些模式的指导下,众多科技情报实践机构在实践领域也产生了一些紧扣时代特点、富有数据特色的情报分析业务系统。中国科学技术信息研究所、中国科学院文献情报中心、北京市科学技术情报研究所、上海科学技术情报研究所、湖南省科学技术信息研究所等情报机构以科技文献、科技管理统计数据、政策文本、科技新闻等数据为基础建立了一系列科技查新系统、科技动态监测、科技统计填报系统、科技决策剧场等情报业务系统,这些系统既有按传统模式建立的独立系统,也有打通了一些多源异构数据、初步运用了数据中台或大数据理念的集成决策系统。同时,数据中台在阿里巴巴、华为等大数据公司的成功应用为科技情报界探索与建设数据中台提供了良好的业务实践与经验参考。数据中台在科技情报领域的应用与建设既有坚实的理论基础,又有紧迫的现实需求,科技情报机构应当重视并加强数据中台的研究与建设。数据中台屏蔽掉底层存储平台的计算技术复杂性,降低对技术人才的需求,让数据的使用成本更低。数据中台包括数据集成汇聚、数据资产管理、数据开发、数据引擎、数据服务、数据运营与安全体系等模块。通过数据中台的数据汇聚、数据开发模块建立数据资产。通过资产管理与治理、数据服务等模块把数据资产变为一种数据服务能力,支撑前端的情报识别与线索发现、科技情报动态监测与跟踪、情报对标与态势分析、科技统计与情报评价、情报研判与预测规划等业务,从而为科技管理、科技规划决策、创新研发等提供完备的信息支撑与情报参考。

With the consecutive accumulation of data resources and the continuous promotion of informatization,many isolated data islands are unexpectedly formed among information systems independently procured or self-built by scientific and technical information institutions with the traditional chimney-type IT construction method.Additionally,in the context of Internet and mobile interconnection,the external data generated under various new modes such as APPs,WeChat subscription accounts,applets,and O2O platforms cannot be interconnected with the internal data of traditional systems,which further exacerbates the problem of data silos.Furthermore,the diversity and polymorphism of systems as well as the multi-source and heterogeneity of data increase the complexity of IT architecture.In order to break down the barriers between the underlying data of system platforms and meet the demands of rapid application deployment,the field of scientific and technological intelligence(STI)has attached great importance to the construction and application of data central-platform.There’s no denying that the rise of big data and the latest development of artificial intelligence have brought new opportunities as well as challenges to information science,which has always emphasized data foundation and the close relationship between STI and artificial intelligence.Under the circumstances,several new patterns have been formed and gradually turned out to be the mainstream of information science over the past decade.The typical examples of them include Engineering Intelligence based on factual data,computational intelligence,quick response intelligence and intelligence 3.0.The in-depth exploration of these researches provides a theoretical basis for the application of data centralplatform in scientific and technological intelligence.Based on the above patterns,lots of relevant institutions have produced a number of information analysis business systems with distinctive features that conform to the characteristics of the times in the field of practice.Institute of Scientific and Technical Information of China,National Science Library of Chinese Academy of Sciences,Beijing Institute of Science and Technology Information,Shanghai Institute of Science and Technology Information,Hunan Institute of Science and Technology Information and other institutions have established a series of effective information business systems,such as the Sci-Tech Novelty Search System and Decision Support System,based on academic literatures,management statistics,policy texts,scientific news and so on.Some of these systems are independent systems established according to the traditional model,and the others are the integrated decision-making systems which have partially fused multi-source heterogeneous data and preliminarily applied the idea of data central-platform or big data.Meanwhile,the successful application of data central-platform in Internet giants,such as Alibaba and Huawei,provides valuable and practical reference for the community of scientific and technological information to explore and build data central-platform.Therefore,the application and construction of data central-platform in the field of scientific and technological intelligence has both a solid theoretical foundation and an urgent practical need,which is imperative for relevant institutions to pay sufficient attention to.The data central-platform can avoid the complex computing technology of the bottom-level data storage platform,thereby reducing the demand for technical talents and the use-cost of data.It consists of several modules such as the data integration and aggregation,data asset management,data development,data engine,data service,data operation and security system.Data assets will be accumulated based on the module of data aggregation and development,and eventually,be transformed into the capability of data service through the process of management and governance.In other words,they will be used to support front-end intelligence identification and insight,dynamic monitoring and tracking of STI,benchmarking and situation analysis,statistics and evaluation as well as prediction and judgment.These achievements can serve as a valuable reference for science and technology management as well as innovative research and development.