Related papers: AstroDS -- A Distributed Storage for Astrophysics …

Cosmic ray data collected by the KASCADE air shower experiment are competitive in terms of quality and statistics with those of modern observatories. We present a novel mass composition analysis based on archival data acquired from 1998 to…

Machine learning has proved to be a useful tool for extracting knowledge from scientific data in numerous research fields, including astrophysics, genomics, and molecular dynamics. Often, data sets from these research areas need to be…

The exponential growth of astronomical data collected by both ground based and space borne instruments has fostered the growth of Astroinformatics: a new discipline laying at the intersection between astronomy, applied computer science, and…

The LHCb collaboration is one of the four major experiments at the Large Hadron Collider at CERN. Many petabytes of data are produced by the detectors and Monte-Carlo simulations. The LHCb Grid interware LHCbDIRAC is used to make data…

Scientific communities naturally tend to organize around data ecosystems created by the combination of their observational devices, their data repositories, and the workflows essential to carry their research from observation to discovery.…

Astronomy produces extremely large data sets from ground-based telescopes, space missions, and simulation. The volume and complexity of these rich data sets require new approaches and advanced tools to understand the information contained…

Most major scientific results produced by ground-based gamma-ray telescopes in the last 30 years have been obtained by expert members of the collaborations operating these instruments. This is due to the proprietary data and software…

Seismology has entered the petabyte era, driven by decades of continuous recordings of broadband networks, the increase in nodal seismic experiments, and the recent emergence of Distributed Acoustic Sensing (DAS). This review explains how…

The ADS All-Sky Survey (ADSASS) is an ongoing effort aimed at turning the NASA Astrophysics Data System (ADS), widely known for its unrivaled value as a literature resource for astronomers, into a data resource. The ADS is not a data…

The Astrophysics Data System (ADS) provides an extensive system of links between the literature and other on-line information. Recently, the journals of the American Astronomical Society (AAS) and a group of NASA data centers have…

Large-scale storage cluster systems need to manage a vast amount of data locations. A naive data locations management maintains pairs of data ID and nodes storing the data in tables. However, it is not practical when the number of pairs is…

Modern materials science generates vast and diverse datasets from both experiments and computations, yet these multi-source, heterogeneous data often remain disconnected in isolated "silos". Here, we introduce MaterialsGalaxy, a…

ESA Gaia mission is producing the more accurate source catalogue in astronomy up to now. That represents a challenge on the archiving area to make accessible this information to the astronomers in an efficient way. Also, new astronomical…

Simulations inform all aspects of modern astrophysical research, ranging in scale from 1D and 2D test problems that can run in seconds on an astronomer's laptop all the way to large-scale 3D calculations that run on the largest…

A wide range of data formats and proprietary software have traditionally been used in gamma-ray astronomy, usually developed for a single specific mission or experiment. However, in recent years there has been an increasing effort towards…

The increase of astronomical data produced by a new generation of observational tools poses the need to distribute data and to bring computation close to the data. Trying to answer this need, we set up a federated data and computing…

The increasing availability of cloud computing services for science has changed the way scientific code can be developed, deployed, and run. Many modern scientific workflows are capable of running on cloud computing resources. Consequently,…

The European Open Science Cloud aims to make all data Findable, Accessible, Interoperable and Reusable. By far the largest community of users of the European Open Science Cloud is the science-inclined public. These users need a more curated…

Data distribution for opportunistic users is challenging as they neither own the computing resources they are using or any nearby storage. Users are motivated to use opportunistic computing to expand their data processing capacity, but they…

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with…