Computational science for a better future

Computational science [1] was introduced and developed as a large multidisciplinary scientific field where multiple areas are joined together. Appearing at the intersection of computer science, information technologies, and mathematical modeling, it provides new methods and tools for researchers in many disciplines, from traditional natural sciences to new applications in medicine, social sciences, and humanities.

Computational science plays an essential role in today’s scientific agenda. First, it continues supporting scientific achievements in diverse domains. Computational models open new horizons in understanding natural and social phenomena on new scales.

Second, it is developing as a solid independent area with its own conceptual and methodological foundation. Computational science combines two principal scientific approaches organized around a computational experiment. The computational experiment is designed and developed in accordance with the domain knowledge and problem definition, forming a deductive or knowledge-based inference of models and computational solutions. On the other hand, the data-driven approaches and methods can be considered inductive (empirical) inference. The combination of these approaches with a wide availability of computational resources gives computational science a boost to develop new and adapt existing general-purpose concepts and technologies. Initially, the research field was based on the intersection of mathematical modeling algorithms (including numerical simulation) and computational-intensive solutions (including high-performance, distributed, or hybrid computing). Currently, the area is developing independently with an additional focus on scalability, openness, and reproducibility [2].

In addition, computational science is widely adopting recent developments in information and computer science technologies. The development of technologies provides new ways to resolve existing issues in the area. For example, there is a large amount of data collected through observation, measurement, or as a result of earlier modeling and simulation. These data provide a significant source for scientific discovery, and some authors consider this a new paradigm (data-intensive scientific discovery as the fourth scientific paradigm) [3]. Together with BigData concepts as a technological backbone, these approaches took their place in the computational science area [4]. Artificial intelligence and machine learning methods recently attracted significant attention within the scientific society and can be considered as another example of such an extension. Within the domain of computational science, these methods may be used for (a) management of complex models; (b) substitute of computationally intensive models; (c) exploration or interpolation of model parameters and data; (d) prediction of model characteristics, including performance, uncertainty, sensitivity, etc. [5], [6], [7], [8].

Third, computational science supports the development of new areas and directions in science, for example, simulation-based engineering science [9] or simulation-based decision-making [10]. Also, one of the important application areas of computational science is multidisciplinary studies, where a combination of models may provide a comprehensive view of the nature of systems and phenomena. For example, the concept of system-level science [11] considers a holistic description of a system to provide the ability for analysis and computational experiments with different goals using the same solution.

With all these aspects, the area of computational science could be considered as one of the drivers for the development of science and technology for a better future by providing novel tools for research and development in crucial areas, by discovering new problems and solving them with novel methods, and by forming completely new approaches for the evolution of the science. With this in mind, we are happy to introduce this special issue formed after the International Conference on Computational Science¹ ICCS 2021 organized under the theme “Computational Science for a Better Future” to tackle the current challenges of our fast-changing world.

Traditionally, ICCS brings together researchers and scientists working in fundamental computer science disciplines and in various application areas, who are pioneering computational methods in sciences such as physics, chemistry, life sciences, and engineering, as well as in arts and humanities. Since its inception in 2001, ICCS forms a space where the problem domains, IT, and modeling join together to discuss the present and future research directions. ICCS is an A-rank² conference in the CORE classification. During the past years, the conference was hosted by a variety of institutions and cities in 12 countries across the globe: Australia, China, Iceland, Poland, Portugal, Russia, the Netherlands, Singapore, Spain, Switzerland, UK, USA. The conference was always focused on recent advances in computational science. Analysis of ICCS topics evolved through its history [12] shows that a significant amount of the works presented at the conference are concentrated around key sub-areas of computational science, including modeling and simulation, high-performance and distributed computing, and numerical methods. Moreover, ICCS reacts to emergent technologies and approaches like the development of GPGPU or IPv6 technologies, which was followed by the growing number of publications in these respective areas.

The ICCS society always attracts both well-known scientists and young researchers. Two years ago, it was our pleasure to announce a special issue of the Journal of Computational Science with 12 selected papers prepared by the leading scientists in the area (acting as keynote speakers during 20 years of ICCS history) and their colleagues, reflecting the vision of issues, recent advances, challenges, and solutions in various sub-areas [13].

Recent advances in data-driven technologies were reflected in the title of ICCS 2014 (“Big Data meets Computational Science”), 2016 (“Data through the Computational Lens”), 2018 (“Science at the Intersection of Data, Modelling, and Computation”). Some of the adaptability of ICCS comes from the thematic tracks and workshops representing the most important topics. Examples of the workshops proudly hosted by ICCS for many years include “Multiscale Modelling and Simulation”, “Computational Optimization, Modelling and Simulation”, “Data-Driven Computational Sciences”, “Agent-Based Simulations, Adaptive Algorithms and Solvers”, “Biomedical and Bioinformatics Challenges”, “Teaching Computational Science”, and many others.