Understanding the emergence, co-evolution, and convergence of science and technology (S&T) areas offers competitive intelligence for researchers, managers, policy makers, and others. The resulting data-driven decision support helps set proper research and development (R&D) priorities; develop future S&T investment strategies; monitor key authors, organizations, or countries; perform effective research program assessment; and implement cutting-edge education/training efforts. This paper presents new funding, publication, and scholarly network metrics and visualizations that were validated via expert surveys. The metrics and visualizations exemplify the emergence and convergence of three areas of strategic interest: artificial intelligence (AI), robotics, and internet of things (IoT) over the last 20 years (1998-2017). For 32,716 publications and 4,497 NSF awards, we identify their conceptual space (using the UCSD map of science), geospatial network, and co-evolution landscape. The findings demonstrate how the transition of knowledge (through cross-discipline publications and citations) and the emergence of new concepts (through term bursting) create a tangible potential for interdisciplinary research and new disciplines.

中文翻译：

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绘制人工智能、机器人和物联网 20 年来（1998-2017）的共同进化图

了解科学和技术 (S&T) 领域的出现、共同进化和融合可为研究人员、管理人员、政策制定者和其他人提供竞争情报。由此产生的数据驱动决策支持有助于确定适当的研发 (R&D) 优先事项；制定未来的科技投资战略；监控主要作者、组织或国家；进行有效的研究计划评估；并实施前沿教育/培训工作。本文介绍了通过专家调查验证的新资金、出版物和学术网络指标和可视化。指标和可视化体现了过去 20 年（1998-2017 年）三个战略利益领域的出现和融合：人工智能 (AI)、机器人和物联网 (IoT)。对于 32，716 篇出版物和 4,497 项 NSF 奖项，我们确定了它们的概念空间（使用 UCSD 科学地图）、地理空间网络和协同进化景观。研究结果展示了知识的转变（通过跨学科出版物和引用）和新概念的出现（通过术语爆发）如何为跨学科研究和新学科创造切实的潜力。