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A preliminary analysis into the effort required for reproducing computational science scholarly articles.
Home Page: https://reproducibilityproject.github.io/effortly/
License: MIT License
Python 0.46%
Jupyter Notebook 99.54%
effortly's Issues
- include science-parse outputs for the original articles inside
src/original-article-sciparse-outputs
- add PDF's of the original article with the same file name as the reproduced article in a directory
src/orignal-pdfs
- Include full text information about the original article inside the
csv
.
- utilize full text information to build structural features from the original article.
- create
src/
directory and touch src/util,py
.
- add the method used for generating science-parse outputs for the replication reports
- add the method used for downloading the replication reports.
- build a
PyG
graph dataset
- include DOI's of the original articles
- include PDF's of the original article
- Encode the sections "Scope of Reproducibility", "What was easy", "What was difficult".
- Include a
README.md
inside src
to outline the thought process behind encoding the above sections.
- url for obtaining the content
https://rescience.github.io/read/