Related papers: FAIR approach for Low Frequency Radio Astronomy

This paper extends the FAIR (Findable, Accessible, Interoperable, Reusable) guidelines to provide criteria for assessing if software conforms to best practices in open source. By adding 'USE' (User-Centered, Sustainable, Equitable),…

This article reports the outcomes of the FAIRNESS COST Action (CA20108), a coordinated European initiative aimed at advancing micrometeorological data toward compliance with the FAIR (Findable, Accessible, Interoperable, Reusable)…

We introduce Radar DataTree, the first dataset-level framework that extends the WMO FM-301 standard from individual radar volume scans to time-resolved, analysis-ready archives. Weather radar data are among the most scientifically valuable…

Data - arguably the most important product of worldwide materials research investment - are rarely shared. The small and biased proportion of results published are buried in plots and text licensed by journals. This situation wastes…

Ground based low frequency radio interferometers have been developed in the last decade and are providing the scientific community with high quality observations. Conversely, current radioastronomy instruments in space have a poor angular…

It is challenging to determine whether datasets are findable, accessible, interoperable, and reusable (FAIR) because the FAIR Guiding Principles refer to highly idiosyncratic criteria regarding the metadata used to annotate datasets.…

This document focuses on databases disseminating data on (hazardous) substances found on the North American and the European (EU) market. The goal is to analyse the FAIRness (Findability, Accessibility, Interoperability and Reusability) of…

In very-high-energy (VHE) gamma-ray astronomy, the community is converging towards the use of a common open data format, called "Data formats for Gamma-ray Astronomy", for the high-level data products. This format is in use for ground-based…

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…

Life sciences research increasingly requires identifying, accessing, and effectively processing data from an ever-evolving array of information sources on the Linked Open Data (LOD) network. This dynamic landscape places a significant…

Low earth orbit (LEO) satellite systems with sensing functionality are envisioned to facilitate global-coverage service and emerging applications in 6G. Currently, two fundamental challenges, namely, inter-beam interference among users and…

Open science aims to make scientific research processes, tools and results accessible to all scientific communities, creating trust in science and enabling digital competences to be realized in research, leading to increased innovation. It…

The FAIR principles are globally accepted guidelines for improved data management practices with the potential to align data spaces on a global scale. In practice, this is only marginally achieved through the different ways in which…

Reproducibility and replicability of research findings are central to the scientific integrity of epidemiology. In addition, many research questions require combiningdata from multiple sources to achieve adequate statistical power. However,…

The development of a knowledge repository for climate science data is a multidisciplinary effort between the domain experts (climate scientists), data engineers whos skills include design and building a knowledge repository, and machine…

We discuss important aspects of HCI research regarding Research Data Management (RDM) to achieve better publication processes and higher reuse of HCI research results. Various context elements of RDM for HCI are discussed, including…

While the FAIR principles are well accepted in the scientific community, the implementation of appropriate metadata editing and transfer to ensure FAIR research data in practice is significantly lagging behind. On the one hand, it strongly…

Precise aerial radio environment characterization is vital for low-altitude planning. However, existing datasets and estimation methods lack the high-resolution granularity required for complex aerial spaces. Additionally, current schemes…

Large-scale science instruments, such as the distributed radio telescope LOFAR, show that we are in an era of data-intensive scientific discovery. Such instruments rely critically on significant computing resources, both hardware and…

Guidelines for managing scientific data have been established under the FAIR principles requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data…