New bibliometric indicators for prospectivity estimation of research fields

Abstract

The paper suggests differential metrics for estimation of change dynamics of major ICT fields using the bibliometric indicators (publication and citation count). It refers to research areas such as big data, computational biology, cloud computing, cyber-physical systems, embedded systems, information security, internet of things, human-machine systems, mobile computing, machine learning, machine-to-machine, multi-agent systems, neural networks, robotics, visualization, augmented reality, SDN, 5G, e-Governance, smart city and smart grid. As supplements to the known indicators, two kinds of integrated derivative-based indicators are suggested. The calculation of indicators is made and their time curve is given. The suggested indicators allow evidently expressing the changes in the dynamics of bibliometric indicators, which can be useful in prospectivity estimation of areas of research.