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Data analysis in space sciences has been performed exclusively visually for years, despite the fact that the largest amount of data belongs to non-visible portions of the electromagnetic spectrum. This, on the one hand, limits the study of…
Data acquisition and analysis for the CODALEMA experiment, in operation for more than one year, has provided improved knowledge of the characteristics of this new device. At the same time, an important effort has been made to develop…
Studies of different term extractors on a corpus of the biomedical domain revealed decreasing performances when applied to highly technical texts. The difficulty or impossibility of customising them to new domains is an additional…
The Big Data landscape poses challenges in managing diverse data formats, requiring efficient storage and processing for high-quality analysis. Effective metadata management is crucial for organizing, accessing, and reusing data within…
Modern soft X-ray observatories can yield unique insights into time domain astrophysics, and a huge amount of information is stored - and largely unexploited - in data archives. Like a treasure-hunt, the EXTraS project harvested the…
Large-scale scientific collaborations, such as the Compact Muon Solenoid (CMS) at CERN, produce a vast and ever-growing corpus of internal documentation. Navigating this complex information landscape presents a significant challenge for…
As current- and next-generation astronomical instruments come online, they will generate an unprecedented deluge of data. Analyzing these data in real time presents unique conceptual and computational challenges, and their long-term storage…
Tens of millions of new variable objects are expected to be identified in over a billion time series from the Gaia mission. Crossmatching known variable sources with those from Gaia is crucial to incorporate current knowledge, understand…
Data collection is an important part of many citizen science projects as well as other fields of research, particularly in life sciences. Mobile applications with form-based surveys are increasingly used to support this, due to the large…
Before the publication of the Gaia Catalogue, the contents of the first data release have undergone multiple dedicated validation tests. These tests aim at analysing in-depth the Catalogue content to detect anomalies, individual problems in…
Astrophysics and cosmology are rich with data. The advent of wide-area digital cameras on large aperture telescopes has led to ever more ambitious surveys of the sky. Data volumes of entire surveys a decade ago can now be acquired in a…
This paper corresponds to an invited oral contribution to the session 5A organised by the IAU inter-commission B2-B5 working group (WG) "Laboratory Astrophysics Data Compilation, Validation and Standardization: from the Laboratory to FAIR…
Meta-software for data acquisition (DAQ) is a new approach to design the DAQ systems for experimental setups in experiments in high energy physics (HEP). It abstracts from experiment-specific data processing logic, but reflects it through…
The increasing complexity of the software/hardware stack of modern supercomputers results in explosion of parameters. The performance analysis becomes a truly experimental science, even more challenging in the presence of massive…
This paper describes a new approach to the optimization of information extraction in multi-wavelength image cubes of cosmological fields. The objective is to create a framework for the automatic identification and tagging of sources…
The Galactica simulation database is a platform designed to assist computational astrophysicists with their open science approach based on FAIR (Findable, Accessible, Interoperable, Reusable) principles. It offers the means to publish their…
Metadata management plays a critical role in data governance, resource discovery, and decision-making in the data-driven era. While traditional metadata approaches have primarily focused on organization, classification, and resource reuse,…
Context. In the current ever increasing data volumes of astronomical surveys, automated methods are essential. Objects of known classes from the literature are necessary for training supervised machine learning algorithms, as well as for…
The standardisation of gamma-ray astronomical data emerged in recent years as a necessity for the future generation of gamma-ray observatories. Nevertheless, adopting a common format for gamma-ray instruments can already benefit the current…
Data lakes have emerged as an alternative to data warehouses for the storage, exploration and analysis of big data. In a data lake, data are stored in a raw state and bear no explicit schema. Thence, an efficient metadata system is…