大数据时代的技术情报工程  

Introduction of Technology Intelligence Engineering in Big Data Era

作　　者：乔晓东 朱礼军 李颖 徐硕 韩红旗 

机构地区：[1]中国科学技术信心研究所,北京100038

出　　处：《情报学报》2014年第12期1255-1263,共9页Journal of the China Society for Scientific and Technical Information

基　　金：国家“十二五”科技支撑计划课题“技术创新服务平台关键技术研究与应用示范”（2011BAH30B01）资助.

摘　　要：大数据时代，科技情报工作面临着数据存储和处理云端化、计算能力云端化和专家决策智能化等诸多挑战。为应对这些挑战，本文认为情报处理和分析工作应以工程化和系统化的思路开展，进而提出了技术情报工程的理念和以技术基础设施为支撑的情报分析体系，使得分布在云端的事实型数据资源可以集成融合、情报分析工具可以组装配置、专家可以协同决策，从而丰富了“事实数据＋工具方法＋专家智慧”方法的内涵。最后，以技术洞察和技术创新服务平台为例，对这一新的工作体系进行了详细诠释。希望本研究能为大数据时代的科技情报工作提供新思路，为构建我国科技信息服务业的生态环境和解决创新型国家顶层设计的重大需求提供借鉴。Under Big Data Era, science and technology information service is facing the challenges of Data Storage ＆amp; Process as a Service, Computing Power as a Service, and Specialist Wisdom as a Service. To tackle such problems, this article argues that information processing and analysis should be undertaken by engineering and systematic patterns, and proposes the ideas of Technology Intelligence Engineering and intelligence analysis system supported by technology infrastructure, which is named as FAST4Wisdom. It can make factual data resources are integrated, specified tools assembled and configured, and specialists coordinated in cloud hosting services. Consequently it can enrich our previous “Factual data ＋ Specified tool ＋Specialist wisdom” method. Finally, this article illustrates the new system of Technology Intelligence Engineering by two important cases; they are the Technology Insight and the Industry oriented Technology Innovation Service Platform. Our R＆amp;Ds are supposed to provide a creative idea for science and technology information service under the Big Data Era, and contribute to ecology of science and technology information industry and the top design of an innovative country for China.

关 键 词：“事实型数据+专用工具+专家智慧” 技术情报工程 FAST4Wisdom 大数据 技术基础设施 

分 类 号：G359.224[文化科学—情报学]