  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.
