Computational Science - Research Assessment and Interdisciplinary Methods

Computational Science is a rapidly growing, multi-, and interdisciplinary field that develops mathematical and computational models and uses advanced computing techniques to simulate these models, driven by data. The overarching goal of computational science is to understand and solve complex problems. It has reached a level of predictive and interventional capability that firmly complements the traditional pillars of experimentation and theory. The resulting data explosion allows for detailed data-driven modelling and simulation, which is no longer feasible using traditional analytical approaches alone. This combines computational thinking, modern computational methods, devices, and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements:

• Modelling, Algorithms, and Simulations (e.g., numerical and non-numerical, discrete and continuous);

• Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems;

• Computer and information science that develops and optimizes advanced system hardware, software, networking, and data management components (e.g., problem-solving environments).

We would also be keen to see work on new methods/techniques for analyzing data/information and possible new frameworks to be developed and proposed.

Keywords: Computer Vision, Machine learning, AI, Deep learning, Augmented learning, Computational techniques, Modelling, Algorithms, Simulations, Software, Agribusiness innovation, Smart Cities

Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.