Related papers: Data discovery, analysis and reproducibility in Vi…
The Virtual Research Environment is an analysis platform developed at CERN serving the needs of scientific communities involved in European Projects. Its scope is to facilitate the development of end-to-end physics workflows, providing…
Virtual Research Environments (VREs) provide user-centric support in the lifecycle of research activities, e.g., discovering and accessing research assets, or composing and executing application workflows. A typical VRE is often implemented…
In complex data analyses it is increasingly important to capture information about the usage of data sets in addition to their preservation over time to ensure reproducibility of results, to verify the work of others and to ensure…
Many research groups aspire to make data and code FAIR and reproducible, yet struggle because the data and code life cycles are disconnected, executable environments are often missing from published work, and technical skill requirements…
Data analysis in fundamental sciences nowadays is an essential process that pushes frontiers of our knowledge and leads to new discoveries. At the same time we can see that complexity of those analyses increases fast due to a)~enormous…
Modern science clearly demands for a higher level of reproducibility and collaboration. To make research fully reproducible one has to take care of several aspects: research protocol description, data access, environment preservation,…
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…
Existing prompt-optimization techniques rely on local signals to update behavior, often neglecting broader and recurring patterns across tasks, leading to poor generalization; they further rely on full-prompt rewrites or unstructured…
We develop an open-source Python software integrating flexibility needs from Variable Renewable Energies (VREs) in the development of regional energy mixes. It provides a flexible and extensible tool to researchers/engineers, and for…
The information retrieval (IR) community has a strong tradition of making the computational artifacts and resources available for future reuse, allowing the validation of experimental results. Besides the actual test collections, the…
Computational experiments have become essential for scientific discovery, allowing researchers to test hypotheses, analyze complex datasets, and validate findings. However, as computational experiments grow in scale and complexity, ensuring…
The Collaborative Analysis Versioning Environment System (CAVES) project concentrates on the interactions between users performing data and/or computing intensive analyses on large data sets, as encountered in many contemporary scientific…
Interactive notebooks, such as Jupyter, have revolutionized the field of data science by providing an integrated environment for data, code, and documentation. However, their adoption by robotics researchers and model developers has been…
Through its affordances, immersive virtual reality (VR) offers a means to apply embodied and external cognition from the physical realm to solving analytical problems that are typically only conceptual. We present an example of executing a…
We present RCE (Remote Component Environment), an open-source framework developed primarily at DLR (German Aerospace Center) that enables its users to construct and execute multidisciplinary engineering workflows comprising multiple…
The EU ESCAPE project is developing ESAP, ESFRI 1 Scientific Analysis Platform, as an API gateway that enables the seamless integration of independent services accessing distributed data and computing resources. In ESCAPE we are exploring…
We propose an approach for improved reproducibility that includes capturing and relating provenance characteristics and performance metrics, in a hybrid queriable system, the ProvEn server. The system capabilities are illustrated on two use…
We introduce Repro, an open-source library which aims at improving the reproducibility and usability of research code. The library provides a lightweight Python API for running software released by researchers within Docker containers which…
The VERCE project has pioneered an e-Infrastructure to support researchers using established simulation codes on high-performance computers in conjunction with multiple sources of observational data. This is accessed and organised via the…
OpenNRE is an open-source and extensible toolkit that provides a unified framework to implement neural models for relation extraction (RE). Specifically, by implementing typical RE methods, OpenNRE not only allows developers to train custom…