English

CLAIMED -- the open source framework for building coarse-grained operators for accelerated discovery in science

Artificial Intelligence 2023-07-14 v1 Databases Machine Learning

Abstract

In modern data-driven science, reproducibility and reusability are key challenges. Scientists are well skilled in the process from data to publication. Although some publication channels require source code and data to be made accessible, rerunning and verifying experiments is usually hard due to a lack of standards. Therefore, reusing existing scientific data processing code from state-of-the-art research is hard as well. This is why we introduce CLAIMED, which has a proven track record in scientific research for addressing the repeatability and reusability issues in modern data-driven science. CLAIMED is a framework to build reusable operators and scalable scientific workflows by supporting the scientist to draw from previous work by re-composing workflows from existing libraries of coarse-grained scientific operators. Although various implementations exist, CLAIMED is programming language, scientific library, and execution environment agnostic.

Keywords

Cite

@article{arxiv.2307.06824,
  title  = {CLAIMED -- the open source framework for building coarse-grained operators for accelerated discovery in science},
  author = {Romeo Kienzler and Rafflesia Khan and Jerome Nilmeier and Ivan Nesic and Ibrahim Haddad},
  journal= {arXiv preprint arXiv:2307.06824},
  year   = {2023}
}

Comments

Received IEEE OSS Award 2023 - https://conferences.computer.org/services/2023/symposia/oss.html

R2 v1 2026-06-28T11:29:31.777Z