相关论文: openDaVE - a data visualisation and transformation…
Software visualization helps to comprehend the system by providing a vivid illustration. The developers, as well as the analysts, can have a glance over the total system to understand the basic changes over time from a high-level point of…
The discovery of new materials as well as the determination of a vast set of materials properties for science and technology is a fast growing field of research, with contributions from many groups worldwide. Materials data from individual…
The FAIR Principles are a set of good practices to improve the reproducibility and quality of data in an Open Science context. Different sets of indicators have been proposed to evaluate the FAIRness of digital objects, including datasets…
We introduce Docling, an easy-to-use, self-contained, MIT-licensed, open-source toolkit for document conversion, that can parse several types of popular document formats into a unified, richly structured representation. It is powered by…
We report on an exploratory project aimed at performing immersive 3D visualization of astronomical data, starting with spectral-line radio data cubes from galaxies. This work is done as a collaboration between the Department of Physics and…
Distributed Real-Time (DRT) systems are among the most complex software systems to design, test, maintain and evolve. The existence of components distributed over a network often conflicts with real-time requirements, leading to design…
A large number of computational scientific research projects make use of open source software packages. However, the development process of such tools frequently differs from conventional software development; partly because of the nature…
Open source software development, particularly within institutions such as universities and research laboratories, is often decentralized and difficult to track. Although academic teams produce many impactful scientific tools, their…
Particle accelerator projects share many characteristics with industrial projects. However, experience has shown that best practice of industrial project management is not always well suited to particle accelerator projects. Major…
OpenRefine is a popular open-source data cleaning tool. It allows users to export a previously executed data cleaning workflow in a JSON format for possible reuse on other datasets. We have developed or2yw, a novel tool that maps a…
Neural audio processing has unlocked novel methods of sound transformation and synthesis, yet integrating deep learning models into digital audio workstations (DAWs) remains challenging due to real-time / neural network inference…
Access to molecular and atomic data is critical for many forms of remote sensing analysis across different fields. Many atomic and molecular databases are however highly specialized for their intended application, complicating querying and…
Application developers, in our experience, tend to hesitate when dealing with linked data technologies. To reduce their initial hurdle and enable rapid prototyping, we propose in this paper a framework for building linked data applications.…
An adventure at engineering design and modeling is possible with a Virtual Reality Environment (VRE) that uses multiple computer-generated media to let a user experience situations that are temporally and spatially prohibiting. In this…
The growth of computational astrophysics and complexity of multidimensional datasets evidences the need for new versatile visualization tools for both analysis and presentation of the data. In this work we show how to use the open source…
We present the beta release of iDaVIE-v, a new Virtual Reality software for data cube exploration. The beta release of iDaVIE-v (immersive Data Visualisation Interactive Explorer for volumetric rendering) is planned for release in early…
The recent explosion of recorded digital data and its processed derivatives threatens to overwhelm researchers when analysing their experimental data or when looking up data items in archives and file systems. While current hardware…
Data warehouses are overwhelmingly built through a bottom-up process, which starts with the identification of sources, continues with the extraction and transformation of data from these sources, and then loads the data into a set of data…
Labeled datasets are essential for supervised machine learning. Various data labeling tools have been built to collect labels in different usage scenarios. However, developing labeling tools is time-consuming, costly, and…
Recent advances in computing hardware and modeling software have given rise to new applications for numerical optimization. These new applications occasionally uncover bottlenecks in existing optimization algorithms and necessitate further…