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For the successful development of the astrophysics and, accordingly, for obtaining more complete knowledge of the Universe, it is extremely important to combine and comprehensively analyze information of various types (e.g., about charged…

The CMS experiment at the CERN LHC developed the Workflow Management Archive system to persistently store unstructured framework job report documents produced by distributed workflow management agents. In this paper we present its…

Data from high-energy physics experiments are collected with significant financial and human effort and are mostly unique. However, until recently no coherent strategy existed for data preservation and re-use, and many important and complex…

The recent explosion of recorded digital data and its processed derivatives threatens to overwhelm researchers when analysing their experimental data or when looking up data items in archives and file systems. While current hardware…

The Large Hadron Collider (LHC) at CERN has generated in the last decade an unprecedented volume of data for the High-Energy Physics (HEP) field. Scientific collaborations interested in analysing such data very often require computing power…

Modern science and engineering computing environments often feature storage systems of different types, from parallel file systems in high-performance computing centers to object stores operated by cloud providers. To enable easy, reliable,…

In the current era of Big Data, data engineering has transformed into an essential field of study across many branches of science. Advancements in Artificial Intelligence (AI) have broadened the scope of data engineering and opened up new…

As storage systems become increasingly heterogeneous and complex, it adds burdens on DBAs, causing suboptimal performance even after a lot of human efforts have been made. In addition, existing monitoring-based storage management by access…

In High Energy Physics (HEP), experimentalists generate large volumes of data that, when analyzed, helps us better understand the fundamental particles and their interactions. This data is often captured in many files of small size,…

Data preservation significantly increases the scientific output of high-energy physics experiments during and after data acquisition. For new and ongoing experiments, the careful consideration of long-term data preservation in the…

Data collected by large-scale instruments, observatories, and sensor networks are key enablers of scientific discoveries in many disciplines. However, ensuring that these data can be accessed, integrated, and analyzed in a democratized and…

Data-intensive applications often require exploratory analysis of large datasets. If analysis is performed on distributed resources, data locality can be crucial to high throughput and performance. We propose a "data diffusion" approach…

Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and…

Today's world of scientific software for High Energy Physics (HEP) is powered by x86 code, while the future will be much more reliant on accelerators like GPUs and FPGAs. The portable parallelization strategies (PPS) project of the High…

Objective: To (1) demonstrate the implementation of a data science platform built on open-source technology within a large, academic healthcare system and (2) describe two computational healthcare applications built on such a platform.…

Handling, processing and archiving the huge amount of data produced by the new generation of experiments and instruments in Astronomy and Astrophysics are among the more exciting challenges to address in designing the future data management…

Advances in technology and computing hardware are enabling scientists from all areas of science to produce massive amounts of data using large-scale simulations or observational facilities. In this era of data deluge, effective coordination…

The H1 data preservation project was started in 2009 as part of the global data preservation initiative in high-energy physics, DPHEP. In order to retain the full potential for future improvements, the H1 Collaboration aims for level 4 of…

Hydrogen storage remains a central bottleneck for scalable hydrogen energy systems due to the multiscale and coupled nature of the thermodynamics, kinetics, and microstructural evolution of hydrogen storage materials (HSMs). Although…

Wireless edge networks in smart industrial environments increasingly operate using advanced sensors and autonomous machines interacting with each other and generating huge amounts of data. Those huge amounts of data are bound to make data…