相关论文: Building an interoperable, distributed storage and…

Scientific collaborations require a strong computing infrastructure to successfully process and analyze data. While large-scale collaborations have access to resources such as Analysis Facilities, small-scale collaborations often lack the…

Intelligent Transport Systems are crucial in the digital transformation of transportation. The EC mandates the establishment of National Access Points (NAPs) in each Member State, serving as common national interfaces for ITS data exchange.…

In the coming era of data-intensive science, it will be increasingly important to be able to seamlessly move between scientific results, the data analyzed in them, and the processes used to produce them. As observations, derived data…

Laboratory testbeds are an integral part of conducting research and developing technology for high-contrast imaging and extreme adaptive optics. There are a number of laboratory groups around the world that use and develop resources that…

Today, modern unmanned aerial vehicles (UAVs) are equipped with increasingly advanced capabilities that can run applications enabled by machine learning techniques, which require computationally intensive operations such as matrix…

The new NASA Astrophysics Data System (ADS) is designed with a serviceoriented architecture (SOA) that consists of multiple customized Apache Solr search engine instances plus a collection of microservices, containerized using Docker, and…

We present technical, instrumental, and software upgrades completed and planned at astronomical observatory called "Osservatorio Astronomico Regionale Parco Antola, Fascia" (OARPAF), hosting an 80cm, alt-az Cassegrain-Nasmyth telescope. The…

We review some aspects of the current state of data-intensive astronomy, its methods, and some outstanding data analysis challenges. Astronomy is at the forefront of "big data" science, with exponentially growing data volumes and data…

The big data processing in distributed Internet of Things (IoT) systems calls for innovative computing architectures and resource provisioning techniques to support real-time and cost-effective computing services. This article introduces a…

Recently, a number of cloud platforms and services have been developed for data intensive computing, including Hadoop, Sector, CloudStore (formerly KFS), HBase, and Thrift. In order to benchmark the performance of these systems, to…

The rapid growth of Artificial Intelligence and Machine Learning in scientific research has highlighted a gap between industry-standard MLOps tools and platforms, and the unique requirements of modern and Open Science, particularly…

There is a widespread interest to digitize the precious information contained in the astronomical plate archives, both for the preservation of their content and for its fast distribution to all interested researchers in order to achieve…

As telecommunications systems progress to support diverse use cases with heterogeneous and dynamic Quality of Service (QoS) requirements, it becomes an increasingly complex task to automatically manage various resources involved -- from…

In the immediate future holographic technology will be available to store a very large amount of data in HVD (Holographic Versatile Disk) devices. This technology make extensive use of the WORM (Write-Once-Read-Many) paradigm: this means…

In recent years, cloud storage technology has been widely used in many fields such as education, business, medical and more because of its convenience and low cost. With the widespread applications of cloud storage technology, data access…

To help facilitate expertise in IoT technologies, NLeSC and SURF worked together on a project focusing on IoT applications and platforms. The information included in this case study show the results of NLeSC and SURF's investigation,…

A spectrum-sharing satellite-ground integrated network is conceived, consisting of a pair of non-geostationary orbit (NGSO) constellations and multiple terrestrial base stations, which impose the co-frequency interference (CFI) on each…

The VESPA data access system focuses on applying Virtual Observatory (VO) standards and tools to Planetary Science. Building on a previous EC-funded Europlanet program, it has reached maturity during the first year of a new Europlanet 2020…

AEROS aims to develop a nanosatellite as a precursor of a future system of systems, which will include assets and capabilities of both new and existing platforms operating in the Ocean and Space, equipped with state-of-the-art sensors and…

The start of data taking at the Large Hadron Collider will herald a new era in data volumes and distributed processing in particle physics. Data volumes of hundreds of Terabytes will be shipped to Tier-2 centres for analysis by the LHC…