Related papers: FAIR solutions for a science platform to analyse C…
Addressing the challenges posed by climate change, biodiversity loss, and environmental pollution requires comprehensive monitoring and effective data management strategies that are applicable across various scales in environmental system…
Simulating and analysing detailed observations of astrophysical sources for very high energy (VHE) experiments, like the Cherenkov Telescope Array (CTA), can be a demanding task especially in terms of CPU consumption and required storage.…
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…
The International Virtual Observatory Alliance (IVOA) has developed and built, in the last two decades, an ecosystem of distributed resources, interoperable and based upon open shared technological standards. In doing so the IVOA has…
The U.S. Virtual Astronomical Observatory was a software infrastructure and development project designed both to begin the establishment of an operational Virtual Observatory (VO) and to provide the U.S. coordination with the international…
Accessing research data at any time is what FAIR (Findable Accessible Interoperable Reusable) data sharing aims to achieve at scale. Yet, we argue that it is not sustainable to keep accumulating and maintaining all datasets for rapid…
Data access and interoperability module connects the observation proposals, data, virtual machines and software. According to the unique identifier of PI (principal investigator), an email address or an internal ID, data can be collected by…
The availability of open data and of tools to create visualizations on top of these open datasets have led to an ever-growing amount of geovisualizations on the Web. There is thus an increasing need for techniques to make geovisualizations…
The Cherenkov Telescope Array (CTA), a ground-based facility for very-high-energy (VHE) gamma-ray astronomy, will operate as an open observatory, serving a wide scientific community to explore and to study the non-thermal universe. Open…
FAIR data presupposes their successful communication between machines and humans while preserving their meaning and reference, requiring all parties involved to share the same background knowledge. Inspired by English as a natural language,…
The prosperity and lifestyle of our society are very much governed by achievements in condensed matter physics, chemistry and materials science, because new products for sectors such as energy, the environment, health, mobility and…
We developed several pieces of software to enable the tracking of provenance information for the large-scale complex astronomical observatory CTA, the Cherenkov Telescope Array. Such major facilities produce data that will be publicly…
The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research…
In the ever-changing realm of research software development, it is crucial for the scientific community to grasp current trends to identify gaps that can potentially hinder scientific progress. The adherence to the FAIR (Findable,…
Operation of the US Virtual Astronomical Observatory shares some issues with modern physical observatories, e.g., intimidating data volumes and rapid technological change, and must also address unique concerns like the lack of direct…
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…
Computational workflows represent major investments of effort and expertise. As first-class, publishable research objects of their own, they are key to sharing methodological know-how for reuse, reproducibility, and transparency. Thus, the…
The FAIR principles define a number of expected behaviours for the data and services ecosystem with the goal of improving the findability, accessibility, interoperability, and reusability of digital objects. A key aspiration of the…
The Hybrid Technology Hub and many other research centers work in cross-functional teams whose workflow is not necessarily linear and where in many cases technology advances are done through parallel work. The lack of proper tools and…
The rapid growth of Artificial Intelligence and Machine Learning in scientific research has highlighted a gap between industry-standard MLOps tools and platforms, and the unique requirements of modern and Open Science, particularly…