Due to popular successes (eg, ChatGPT) Artificial Intelligence (AI) is on everyone's lips
today. When advances in biotechnology are combined with advances in AI unprecedented …

Research software is a fundamental and vital part of research, yet significant challenges to
discoverability, productivity, quality, reproducibility, and sustainability exist. Improving the …

Despite peatlands' important feedbacks on the climate and global biogeochemical cycles,
predicting their dynamics involves many uncertainties and an overwhelming variety of …

Over the last decades, model predictive control (MPC) has shown outstanding performance
for control tasks from various domains. This performance has further improved in recent …

Understanding how society can address and mitigate threats to groundwater sustainability
remains a pressing challenge in the Anthropocene era. This article presents the first …

Research data is accumulating rapidly and with it the challenge of fully reproducible
science. As a consequence, implementation of high-quality management of scientific data …

Computational modeling has become a valuable tool for science and policy, but community
standards to share model details have not kept pace. For research to be replicated …

The main goals and challenges for the life science communities in the Open Science
framework are to increase reuse and sustainability of data resources, software tools, and …

Scientific workflows have become integral tools in broad scientific computing use cases.
Science discovery is increasingly dependent on workflows to orchestrate large and complex …

A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles
were proposed in 2016 as prerequisites for proper data management and stewardship, with …