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In computational science and in computer science, research software is a central asset for research. Computational science is the application of computer science and software engineering principles to solving scientific problems, whereas…
Models are the primary artifacts of model-driven software engineering (MDSD) [1], and a terminal model is a representation that conforms to a given software metamodel [2, 3]. As the quality of a software metamodel directly impacts the…
In materials sciences, a large amount of research data is generated through a broad spectrum of different experiments. As of today, experimental research data including meta-data in materials science is often stored decentralized by the…
Quality assessment of Research Software Engineering (RSE) plays an important role in all scientific fields. From the canonical three criteria (reliability, validity, and objectivity) previous research has focussed on reliability and the…
Algorithmic bias mitigation has been one of the most difficult conundrums for the data science community and Machine Learning (ML) experts. Over several years, there have appeared enormous efforts in the field of fairness in ML. Despite the…
Synthesis procedures play a critical role in materials research, as they directly affect material properties. With data-driven approaches increasingly accelerating materials discovery, there is growing interest in extracting synthesis…
Machine learning (ML) is an increasingly important scientific tool supporting decision making and knowledge generation in numerous fields. With this, it also becomes more and more important that the results of ML experiments are…
The landscape of workflow systems for scientific applications is notoriously convoluted with hundreds of seemingly equivalent workflow systems, many isolated research claims, and a steep learning curve. To address some of these challenges…
One of the difficulties of artificial intelligence is to ensure that model decisions are fair and free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and mitigate algorithmic unfairness and bias. This…
Quantum technologies are poised to move the foundational principles of quantum physics to the forefront of applications. This roadmap identifies some of the key challenges and provides insights on materials innovations underlying a range of…
This survey aims at providing a comprehensive overview of the recent trends in the field of modeling and simulation (M&S) of interactions between users and recommender systems and applications of the M&S to the performance improvement of…
FAIR Digital Object (FDO) is an emerging concept that is highlighted by European Open Science Cloud (EOSC) as a potential candidate for building a ecosystem of machine-actionable research outputs. In this work we systematically evaluate FDO…
Coupling separately developed codes offers an attractive method for increasing the accuracy and fidelity of the computational models. Examples include the earth sciences and fusion integrated modeling. This paper describes the Framework…
Machine learning (ML) algorithms are increasingly deployed to make critical decisions in socioeconomic applications such as finance, criminal justice, and autonomous driving. However, due to their data-driven and pattern-seeking nature, ML…
In recent years, there has been a stimulating discussion on how artificial intelligence (AI) can support the science and engineering of intelligent educational applications. Many studies in the field are proposing actionable data mining…
This paper introduces the Fair Fairness Benchmark (\textsf{FFB}), a benchmarking framework for in-processing group fairness methods. Ensuring fairness in machine learning is important for ethical compliance. However, there exist challenges…
Cycle-accurate software simulation of multicores with complex microarchitectures is often excruciatingly slow. People use simplified core models to gain simulation speed. However, a persistent question is to what extent the results derived…
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…
Research data and software are widely accepted as an outcome of scientific work. However, in comparison to text-based publications, there is not yet an established process to assess and evaluate quality of research data and research…
Course-based Undergraduate Research Experiences (CUREs) bring the excitement of research into the classroom to improve learning and the sense of belonging in the field. They can reach more students, earlier in their studies, than typical…