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The mining of Virtual Observatories (VOs) is becoming a powerful new method for discovery in astronomy. Here we report on the development of SkyDOT (Sky Database for Objects in the Time domain), a new Virtual Observatory, which is dedicated…
Access to astronomical data through archives and VO is essential but does not solve all problems. Availability of appropriate software for analyzing the data is often equally important for the efficiency with which a researcher can publish…
We present DAO Portal, a production-grade analytics pipeline and interactive dashboard for assessing the sustainability of Decentralised Autonomous Organisations (DAOs) through Key Performance Indicators (KPIs) derived from on-chain…
We present the Gaia-Groundbased Observational Service for Asteroids (GOSA). Gaia-GOSA is an interactive tool which supports observers in planning photometric observations of asteroids. Each user is able to personalise the observation plan…
The world astronomical image archives represent huge opportunities to time-domain astronomy sciences and other hot topics such as space defense, and astronomical observatories should improve this wealth and make it more accessible in the…
KYA (Know Your Agents) is an open-source, framework-agnostic trust and governance layer for autonomous systems, composed of five primitives: (1) a four-gate inbound apply pipeline; (2) an only-tighten composition algebra over 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…
The coffea framework provides a new approach to High-Energy Physics analysis, via columnar operations, that improves time-to-insight, scalability, portability, and reproducibility of analysis. It is implemented with the Python programming…
The VIALACTEA project has a work package dedicated to Tools and Infrastructure and, inside it, a task for the Database and Virtual Observatory Infrastructure. This task aims at providing an infrastructure to store all the resources needed…
CapyMOA is an open-source Python library for efficient machine learning on data streams and online continual learning. It provides a structured framework for real-time learning, supporting adaptive models that evolve over time. CapyMOA's…
Nowadays, many scientific areas share the same broad requirements of being able to deal with massive and distributed datasets while, when possible, being integrated with services and applications. In order to solve the growing gap between…
A Virtual Observatory (VO) will enable transparent and efficient access, search, retrieval, and visualization of data across multiple data repositories, which are generally heterogeneous and distributed. Aspects of data mining that apply to…
This paper presents the Kafka Slurm Agent (KSA), an open source (Apache 2.0 license) distributed computing and stream processing engine designed to help researchers distribute Python-based computational tasks across multiple Slurm-managed…
I present here a review of past and present multi-disciplinary research of the Pittsburgh Computational AstroStatistics (PiCA) group. This group is dedicated to developing fast and efficient statistical algorithms for analysing huge…
The Kieker observability framework is a tool that provides users with the means to design a custom observability pipeline for their application. Originally tailored for Java, supporting Python with Kieker is worthwhile. Python's popularity…
The Sloan Digital Sky Survey Science Archive is the first in a series of multi-Terabyte digital archives in Astronomy and other data-intensive sciences. To facilitate data mining in the SDSS archive, we adapted a commercial database engine…
The immense volume of data generated by the suite of instruments on SDO requires new tools for efficient identifying and accessing data that is most relevant to research investigations. We have developed the Heliophysics Events…
The increasing adoption of low-cost environmental sensors and AI-enabled applications has accelerated the demand for scalable and resilient data infrastructures, particularly in data-scarce and resource-constrained regions. This paper…
Scientific endeavors such as large astronomical surveys generate databases on the terabyte scale. These, usually multidimensional databases must be visualized and mined in order to find interesting objects or to extract meaningful and…
A recent study showed that more than 70% of researchers fail to reproduce their peers's experiments and more than half fail to reproduce their own experiments. Obviously, from a perspective of scientific quality this is a more than…