Jupyter notebooks as discovery mechanisms for open science: Citation practices in the astronomy community

Using the Jupyter Notebook as a Tool for Open Science: An Empirical Study

As scientific work becomes more computational and data intensive, research processes and results become more difficult to interpret and reproduce. In this poster, we show how the Jupyter notebook, a tool originally designed as a free version of Mathematica notebooks, has evolved to become a robust tool for scientists to share code, associated computation, and documentation.

Reproducible Research is more than Publishing Research Artefacts: A Systematic Analysis of Jupyter Notebooks from Research Articles

With the advent of Open Science, researchers have started to publish their research artefacts (i. e., data, software, and other products of the investigations) in order to allow others to reproduce their investigations. While this publication is beneficial for science in general, it often lacks a comprehensive documentation and completeness with respect to the artefacts. This, in turn, prevents the successful reproduction of the analyses. Typical examples are missing scripts, incomplete datasets or specification of used software. Moreover, issues about licences often create legal concerns. Thi…

生物医学出版物中 Jupyter notebooks 的计算可复现性

Computational reproducibility of Jupyter notebooks from biomedical publications

本研究通过大规模自动挖掘并重新运行生物医学论文关联的 Jupyter notebooks，量化其计算可复现性、分析失败原因，并在两年间重复同一流程以验证研究自身的可复现性。

基于Jupyter材料的计算科学仓库网站纲要

An Outline for a Jupyter-Materials-Based Repository Website Focused on the Computational Sciences

本文提出一个基于Jupyter Notebooks的低成本仓库网站，用于传播计算科学开源教材，支持离线使用，并探讨整合Raspberry Pi以扩大覆盖，旨在解决互联网和电脑访问不平等问题。

CORAL: COde RepresentAtion Learning with Weakly-Supervised Transformers for Analyzing Data Analysis

Large scale analysis of source code, and in particular scientific source code, holds the promise of better understanding the data science process, identifying analytical best practices, and providing insights to the builders of scientific toolkits. However, large corpora have remained unanalyzed in depth, as descriptive labels are absent and require expert domain knowledge to generate. We propose a novel weakly supervised transformer-based architecture for computing joint representations of code from both abstract syntax trees and surrounding natural language comments. We then evaluate the mod…