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Building XR-AI research prototypes requires navigating two largely separate ecosystems. Mainstream XR development relies on C#/C++ and game engines, while AI development is centered on Python. This toolchain fragmentation slows down…
Open Universe for blazars is a set of high-transparency data products for blazar science, and the tools designed to generate them. Blazar astrophysics is becoming increasingly data driven, depending on the integration and combined analysis…
Network complexity is increasing, making network control and orchestration a challenging task. The proliferation of network information and tools for data analytics can provide an important insight into resource provisioning and…
The European Open Science Cloud (EOSC) aims to create a federated environment for hosting and processing research data to support science in all disciplines without geographical boundaries, such that data, software, methods and publications…
The Asteroseismic Modeling Portal (AMP) provides a web-based interface for astronomers to run and view simulations that derive the properties of Sun-like stars from observations of their pulsation frequencies. In this paper, we describe the…
Space-based projects are providing a wealth of high-quality asteroseismic data, including frequencies for a large number of stars showing solar-like oscillations. These data open the prospect for precise determinations of key stellar…
Clustering is an effective tool for astronomical spectral analysis, to mine clustering patterns among data. With the implementation of large sky surveys, many clustering methods have been applied to tackle spectroscopic and photometric data…
Text-to-SQL systems powered by Large Language Models have excelled on academic benchmarks but struggle in complex enterprise environments. The primary limitation lies in their reliance on static schema representations, which fails to…
Training deep networks is expensive and time-consuming with the training period increasing with data size and growth in model parameters. In this paper, we provide a framework for distributed training of deep networks over a cluster of CPUs…
The Earth observation satellites (EOSs) are specially designed to collect images according to user requirements. The agile EOSs (AEOS), with stronger attitude maneuverability, greatly improve the observation capability, while increasing the…
The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters involved in DNN training. Distributed computing platforms…
One of the current opportunities for stellar atmospheric modeling is the interpretation of optical interferometric data of stars. Starting from the robust, open source ATLAS atmospheric code (Kurucz, 1979), we have developed a spherically…
To achieve scalability with today's heterogeneous HPC resources, we need a dramatic shift in our thinking; MPI+X is not enough. Asynchronous Many Task (AMT) runtime systems break down the global barriers imposed by the Bulk Synchronous…
Ares is a modular framework, designed to implement dynamic, reconfigurable, fault-tolerant, read/write and strongly consistent distributed shared memory objects. Recent enhancements of the framework have realized the efficient…
In today's world data is being generated at a high rate due to which it has become inevitable to analyze and quickly get results from this data. Most of the relational databases primarily support SQL querying with a limited support for…
Scopus and the Web of Science have been the foundation for research in the science of science even though these traditional databases systematically underrepresent certain disciplines and world regions. In response, new inclusive databases,…
Efficient searches for electromagnetic counterparts to gravitational wave, high-energy neutrino, and gamma-ray burst events demand rapid processing of image arithmetic and geometry set operations in a database to cross-match galaxy…
We present a science-driven discovery portal for all the ESA Astronomy Missions called ESA Sky that allow users to explore the multi-wavelength sky and to seamlessly retrieve science-ready data in all ESA Astronomy mission archives from a…
A flexible and highly-extensible data assimilation testing suite, named DATeS, is described in this paper. DATeS aims to offer a unified testing environment that allows researchers to compare different data assimilation methodologies and…
The ability of the RDF data model to link data from heterogeneous domains has led to an explosive growth of RDF data. So, evaluating SPARQL queries over large RDF data has been crucial for the semantic web community. However, due to the…