Computing and Software for Big Science

SJR Rank #1,365H-index: 28SJR: 2.055Best quartile: Q1APC: US$3,790
Journal website: aims, scope and author guidelines
Publisher

Springer Nature

Country

Switzerland

Type

journal

SJR by Edition

2022202500.551.11.652.2

Subject Categories

  • Computer Science (miscellaneous)Q1
  • Nuclear and High Energy PhysicsQ1
  • SoftwareQ1

Areas: Computer Science · Physics and Astronomy

Most published research topics

Particle physics theoretical and experimental studiesParticle Detector Development and PerformanceDistributed and Parallel Computing SystemsAdvanced Data Storage TechnologiesScientific Computing and Data ManagementHigh-Energy Particle Collisions ResearchComputational Physics and Python ApplicationsParallel Computing and Optimization TechniquesResearch Data Management PracticesRadiation Detection and Scintillator Technologies

Source: OpenAlex

Publication Statistics

2025 Docs3-Year DocsCitable Docs015304560

Documents per Year

2022202506121824

Detailed Information

ISSN

2510-2044

SJR Best Quartile

Q1

Region

Western Europe

Citations per Document (2 years)

4.70

References per Document

44.64

Coverage

2017-2025

Scope

This single blind peer reviewed journal is dedicated to the publication of high-quality material originating from the collective effort by the scientific community to address the special and ever more demanding computing and software needs of the future. At its core will be particle, astro-particle and nuclear physics, as well as observational astronomy and cosmology, or high-brilliance light sources - fields in which experimental research is increasingly organized in large and global collaborations around large-scale instruments with huge output of data, and typically operating at the very frontier of energy, intensity and detector technology. Facing similar challenges ranging from data reduction, via data sharing, to increasingly data-driven modeling of different facets of the same physical universe, the scientific community requires fundamental and novel concepts for large-scale and collaborative computing and software development, as well as novel algorithms and techniques for data processing. SCOPE: - infrastructures for large-scale, high-throughput computing -related software and development -infrastructure middleware development -data processing, hosting and sharing -novel algorithms for efficient data reconstruction and filtering -software benchmarking and performance assessment -frameworks and software integration -online/offline data quality monitoring -distributed data analysis -deep learning algorithms -event and object classification -data visualization - physics event generation and detector simulation

Metrics from SCImago Journal Rank 2025. View on SCImago