Awesome Scholarly Data Analysis

Awesome Scholarly Data Analysis is a curated collection of resources that can support Scholarly Data analytics. This list ranges from:

  • Datasets, which includes different corpora of papers, citations, authors and others, as well as taxonomies and ontologies of research concepts;
  • Tools for collecting and classifying research papers, information extraction, and visualization; and
  • Venues, Summer Schools, and relevant Associations in the field.

Shubhanshu Mishra from University of Illinois at Urbana-Champaign created this project as a crowdsourced initiative on GitHub in which everyone can contribute.

I found this idea very interesting as it can be used as a point of departure for both experts and newcomers, to start exploring their ideas in the field of Scholarly Data. I then joined this initiative by listing additional resources that I had the opportunity to use in my research.

We hope this list will keep growing and become more comprehensive, so to support practitioners in making their ideas more tangible.

Here you can find some relevant links to the project which include the link to the GitHub repository for collaborating and the link to the official list: