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The design of structural & functional materials for specialized applications is being fueled by rapid advancements in materials synthesis, characterization, manufacturing, with sophisticated computational materials modeling frameworks that…

Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse. At the core of this movement, research objects contain and describe scientific…

Recent regulatory proposals for artificial intelligence emphasize fairness requirements for machine learning models. However, precisely defining the appropriate measure of fairness is challenging due to philosophical, cultural and political…

Artificial Intelligence · Computer Science 2026-02-19 Caleb J. S. Barr , Olivia Erdelyi , Paul D. Docherty , Randolph C. Grace

Metamaterials are artificial materials designed to exhibit effective material parameters that go beyond those found in nature. Composed of unit cells with rich designability that are assembled into multiscale systems, they hold great…

Computational Engineering, Finance, and Science · Computer Science 2023-12-07 Doksoo Lee , Wei Wayne Chen , Liwei Wang , Yu-Chin Chan , Wei Chen

Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts 1) archival and dissemination services for raw and curated data,…

A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable) principles for scientific data is transforming the state-of-practice for data management and stewardship, supporting and enabling discovery and…

Artificial Intelligence · Computer Science 2023-08-21 Nikil Ravi , Pranshu Chaturvedi , E. A. Huerta , Zhengchun Liu , Ryan Chard , Aristana Scourtas , K. J. Schmidt , Kyle Chard , Ben Blaiszik , Ian Foster

Two key issues hindering the transition towards FAIR data science are the poor discoverability and inconsistent instructions for the use of data extractor tools, i.e., how we go from raw data files created by instruments, to accessible…

Data Analysis, Statistics and Probability · Physics 2025-06-24 Matthew L. Evans , Gian-Marco Rignanese , David Elbert , Peter Kraus

Data is a crucial raw material of this century, and the amount of data that has been created in materials science in recent years and is being created every new day is immense. Without a proper infrastructure that allows for collecting and…

Materials Science · Physics 2018-05-15 Claudia Draxl , Matthias Scheffler

The FAIR (Findable, Accessible, Interoperable, and Reusable) data principles have gained significant attention as a means to enhance data sharing, collaboration, and reuse across various domains. Here, we explore the potential benefits of…

Physics and Society · Physics 2025-06-17 Michael Seitz , Nick Garabedian , Ilia Bagov , Christian Greiner

Simulations play a crucial role in the modern scientific process. Yet despite (or due to) this ubiquity, the Data Science community shares neither a comprehensive definition for a "high-quality" study nor a consolidated guide to designing…

Computation · Statistics 2025-05-16 Corrine F Elliott , James PC Duncan , Tiffany M Tang , Merle Behr , Karl Kumbier , Bin Yu

Although simulation represents a major advance in the understanding of problems in complex systems, the field currently does not has standards in place that would guide the reporting of the data underlying each model, the process for model…

Chaotic Dynamics · Physics 2011-12-26 Elias Carvalho , Luciano Andrade , Ricardo Chaim , Ricardo Pietrobon

Computational physics increasingly depends on large simulation datasets generated by software that remains under active development for many years. In such settings, reproducibility requires not only well documented data but also explicit…

Computational Physics · Physics 2026-04-30 Markus Uehlein , Tobias Held , Christopher Seibel , Lukas G. Jonda , Baerbel Rethfeld , Sebastian T. Weber

Just like the scientific data they generate, simulation workflows for research should be findable, accessible, interoperable, and reusable (FAIR). However, while significant progress has been made towards FAIR data, the majority of science…

Digital Libraries · Computer Science 2022-05-04 Martin Hunt , Steven Clark , Daniel Mejia , Saaketh Desai , Alejandro Strachan

Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity and reproducibility that also democratize access to platforms and processing know-how. As…

Domain-specific metadata schemas are essential to improve the findability and reusability of research software and to follow the FAIR4RS principles. However, many domains, including energy research, lack established metadata schemas. To…

Software Engineering · Computer Science 2026-01-15 Stephan Ferenz , Oliver Werth , Astrid Nieße

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…

Context: Fairness in systems has emerged as a critical concern in software engineering, garnering increasing attention as the field has advanced in recent years. While several guidelines have been proposed to address fairness, achieving a…

Software Engineering · Computer Science 2026-01-01 Kessia Nepomuceno , Fabio Petrillo

Metamaterials are artificial materials that are designed to meet unseen properties in nature, such as ultra-stiffness and negative materials indices. In mechanical metamaterial design, three key modalities are typically involved, i.e., 3D…

Machine Learning · Computer Science 2025-06-23 Wangzhi Zhan , Jianpeng Chen , Dongqi Fu , Dawei Zhou

Numerical algorithms and computational tools are instrumental in navigating and addressing complex simulation and data processing tasks. The exponential growth of metadata and parameter-driven simulations has led to an increasing demand for…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-02 Pavan L. Veluvali , Jan Heiland , Peter Benner