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With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates…
We describe collaboration networks consisting of research projects funded by the European Union and the organizations involved in those projects. The networks are of substantial size and complexity, but are important to understand due to…
The distributed computing is done on many systems to solve a large scale problem. The growing of high-speed broadband networks in developed and developing countries, the continual increase in computing power, and the rapid growth of the…
The recent attention towards research and development in cyber-physical energy systems has introduced the necessity of emerging multi-domain co-simulation tools. Different educational, research and industrial efforts have been set to tackle…
Cloud computing has permeated into the information technology industry in the last few years, and it is emerging nowadays in scientific environments. Science user communities are demanding a broad range of computing power to satisfy the…
Advancements in digital technologies have a bootstrapping effect. The past fifty years of technological innovations from the computer architecture community have brought innovations and orders-of-magnitude efficiency improvements that…
This study explores how EU integration, globalisation, and geopolitical disruptions have influenced scientific collaboration among European countries at different stages of EU membership. Specifically, it distinguishes between the EU-14,…
Data has become a critical resource for organizations and society. Yet, it is not always as valuable as it could be since there is no well-defined approach to managing and using it. This article explores the increasing importance of global…
Since the European Union introduced its Circular Economy (CE) Action Plan in 2015, CE research has expanded rapidly. However, the structure of this emerging field - both in terms of its constituent disciplines and researcher dynamics -…
The growth of large-scale AI systems is increasingly constrained by infrastructure limits: power availability, thermal and water constraints, interconnect scaling, memory pressure, data-pipeline throughput, and rapidly escalating lifecycle…
Scientific workflows have become essential for orchestrating complex computational processes across distributed resources, managing large datasets, and ensuring reproducibility in modern research. The Workflows Community Summit 2025, held…
Influenced by the great success of deep learning via cloud computing and the rapid development of edge chips, research in artificial intelligence (AI) has shifted to both of the computing paradigms, i.e., cloud computing and edge computing.…
Centralized clouds processing the large amount of data generated by Internet-of-Things (IoT) can lead to unacceptable latencies for the end user. Against this backdrop, Edge Computing (EC) is an emerging paradigm that can address the…
The edge-cloud continuum has emerged as a transformative paradigm that meets the growing demand for low-latency, scalable, end-to-end service delivery by integrating decentralized edge resources with centralized cloud infrastructures.…
Computer Technology has Revolutionized Science. This has motivated scientists to develop mathematical model to simulate salient features of Physical universe. These models can approximate reality at many levels of scale such as atomic…
Scientific progress has long been understood as recombinant, with breakthroughs arising when existing ideas are joined in new ways. Empirical work in this tradition has focused on the inputs to discovery, asking whether a paper draws…
Evolving smart grids require flexible and adaptive control methods. A harmonized hybrid cyber-physical framework, which considers both physical and cyber layers and ensures adaptability, is one of the critical challenges to enable…
The necessity for complex calculations in high-energy physics and large-scale data analysis has led to the development of computing grids, such as the ALICE computing grid at CERN. These grids outperform traditional supercomputers but…
Smart grid interoperability is the means to achieve the twin green and digital transition but re-mains heterogeneous and fragmented to date. This work presents the first ideas and corner-stones of an Interoperability Roadmap for the Energy…
The explosion of data volumes generated by an increasing number of applications is strongly impacting the evolution of distributed digital infrastructures for data analytics and machine learning (ML). While data analytics used to be mainly…