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The term Data Space, understood as the secure exchange of data in distributed systems, ensuring openness, transparency, decentralization, sovereignty, and interoperability of information, has gained importance during the last years.…
We present a numerical code to simulate maps of Galactic emission in intensity and polarization at microwave frequencies, aiding in the design of Cosmic Microwave Background experiments. This Python code builds on existing efforts to…
Time series data are fundamental for a variety of applications, ranging from financial markets to energy systems. Due to their importance, the number and complexity of tools and methods used for time series analysis is constantly…
Karabo is a versatile Python-based software framework simplifying research with radio astronomy data. It bundles existing software packages into a coherent whole to improve the ease of use of its components. Karabo includes useful…
Thermodynamic models are often vital when characterising complex systems, particularly natural gas, electrolyte, polymer, pharmaceutical and biological systems. However, their implementations have historically been abstruse and cumbersome,…
Space weather is a rapidly growing area not only in scientific and engineering applications but also in physics education and in the interest of the public. We focus especially on space radiation and its impact on space exploration. The…
During more than 17 years of operation in space INTEGRAL telescope has accumulated large data set that contains records of hard X-ray and soft gamma-ray astronomical sources. These data can be re-used in the context of multi-wavelength or…
The visual inspection of image and catalog data continues to be a valuable aspect of astronomical data analysis. As the scale of astronomical image and catalog data continues to grow, visualizing the data becomes increasingly difficult. In…
We discuss the development of a Java toolbox for astronomical time series data. Rather than using methods conventional in astronomy (e.g., power spectrum and cross-correlation analysis) we employ rule discovery techniques commonly used in…
While cities around the world are looking for smart ways to use new advances in data collection, management, and analysis to address their problems, the complex nature of urban issues and the overwhelming amount of available data have posed…
The scientific computing landscape has evolved dramatically in the past few years, with new schemes for organizing and storing data that reflect the growth in size and complexity of astronomical data sets. In response to this changing…
aeon is a unified Python 3 library for all machine learning tasks involving time series. The package contains modules for time series forecasting, classification, extrinsic regression and clustering, as well as a variety of utilities,…
This paper describes the design and implementation of Stingray, a library in Python built to perform time series analysis and related tasks on astronomical light curves. Its core functionality comprises a range of Fourier analysis…
In this work we propose a software platform for the collection, visualization, management and analysis of heterogeneous and multisource data for soil characteristics estimation. The platform is designed in such a way that it can easily…
This study introduces Pedophysics, an open-source Python package designed to facilitate solutions for users who work in the field of soil assessment using near-surface geophysical electromagnetic techniques. At the core of this software is…
The availability and easy access of large scale experimental and computational materials data have enabled the emergence of accelerated development of algorithms and models for materials property prediction, structure prediction, and…
This paper deals about the presentation of a new software RUNEOLE used to provide weather data in buildings physics. RUNEOLE associates three modules leading to the description, the modelling and the generation of weather data. The first…
Big earth science data offers the scientific community great opportunities. Many more studies at large-scales, over long-terms and at high resolution can now be conducted using the rich information collected by remote sensing satellites,…
The flux of cosmic rays in the heliosphere is subjected to variations that are related to the Sun's magnetic activity. To study this effect, updated time series of multichannel observations are needed. Here we present a web application that…
Efficient use of energy is essential for today's supercomputing systems, as energy cost is generally a major component of their operational cost. Research into "green computing" is needed to reduce the environmental impact of running these…