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We present here the Data Explorer tool developed at the ASI Science Data Center (ASDC). This tool is designed to provide an efficient and user-friendly way to display information residing in several catalogs stored in the ASDC servers, to…
This brief overview stresses the importance of laboratory data and theory in analyzing astronomical observations and understanding the physical and chemical processes that drive the astrophysical phenomena in our Universe. This includes…
Astronomy is entering a new era as multiple, large area, digital sky surveys are in production. The resulting datasets are truly remarkable in their own right; however, a revolutionary step arises in the aggregation of complimentary…
Reproducibility remains a central challenge in machine learning (ML), especially in collaborative eScience projects where teams iterate over data, features, and models. Current ML workflows are often dynamic yet fragmented, relying on…
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…
We present the design and first test results of a new FADC-based data acquisition (DAQ) system for the Grande array of the KASCADE-Grande experiment. The original KASCADE experiment at the Forschungszentrum Karlsruhe, Germany, has been…
Resolving the most fundamental questions in cosmology requires simulations that match the scale, fidelity, and physical complexity demanded by next-generation sky surveys. To achieve the realism needed for this critical scientific…
The volume of data generated by modern astronomical telescopes is extremely large and rapidly growing. However, current high-performance data processing architectures/frameworks are not well suited for astronomers because of their…
AstroDS is a distributed storage for Cosmic Ray Astrophysics. The primary goal of Astro DS is to gather data measured by the instruments of various physical experiments such as TAIGA, TUNKA, KASCADE into global storage and provide the users…
The Data Handling Pipeline ("Pipeline") has been developed for the Fermi Gamma-Ray Space Telescope (Fermi) Large Area Telescope (LAT) which launched in June 2008. Since then it has been in use to completely automate the production of data…
This paper proposes a composable "Just in Time Architecture" for Data Science (DS) Pipelines named JITA-4DS and associated resource management techniques for configuring disaggregated data centers (DCs). DCs under our approach are…
Cloud platforms allow users to execute tasks directly from their web browser and are a key enabling technology not only for commerce but also for computational science. Research software is often developed by scientists with limited…
Data is the key asset for organizations and data sharing is lifeline for organization growth; which may lead to data loss. Data leakage is the most critical issue being faced by organizations. In order to mitigate the data leakage issues…
The iLCM project pursues the development of an integrated research environment for the analysis of structured and unstructured data in a "Software as a Service" architecture (SaaS). The research environment addresses requirements for the…
Lossy compression is widely used to reduce storage and I/O costs for large-scale particle datasets in scientific applications such as cosmology, molecular dynamics, and fluid dynamics, where clustering structures (e.g., single-linkage or…
Particle filters are computational techniques for estimating the state of dynamical systems by integrating observational data with model predictions. This work introduces a class of Localized Particle Filters (LPFs) that exploit spatial…
High throughput and low latency data processing is essential for systems requiring live decision making, control, and machine learning-optimized data reduction. We focus on two distinct use cases for in-flight streaming data processing for…
Open clusters are key targets for both Galaxy structure and evolution and stellar physics studies. Since \textit{Gaia} DR2 publication, the discovery of undetected clusters has proven that our samples were not complete. Our aim is to…
Most domains of science are experiencing a paradigm shift due to the advent of a new generation of instruments and detectors which produce data and data streams at an unprecedented rate. The scientific exploitation of these data, namely…
Reducing the environmental footprint of electronics and computing devices requires new tools that empower designers to make informed decisions about sustainability during the design process itself. This is not possible with current tools…