Published December 8, 2021 | Version 0.1
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Novelpy, a python package to measure novelty and disruptiveness in science.

  • 1. BETA, Université de Strasbourg, France

Description

The data used in the paper "Novelpy, a python package to measure novelty and disruptiveness in science." (Pelletier & Wirtz 2022)

This data is a sample of Pubmed Knowledge Graph (PKG) formatted to run novelty indicators using the package Novelpy. Each zip is a folder with a JSON file per year for the analysis. In each JSON file you can find information on a list of papers, here's an exhaustive list of information.

'authors_sample' :

  • PMID: 7472417
  • a02_authorslist: list of authors of the paper with PMID 7472417, AID = Disambiguated ID
  • year: 1995

'Citation_net_sample' :

  • PMID: 7472417
  • refs_pmid_wos: list of PMIDs cited by 7472417
  • year: 1995

'Meshterms_sample' :

  • PMID: 7472417
  • Mesh_year_category: list of meshterms and their year of creation
  • year: 1995

'Ref_Journals_sample' :

  • PMID: 7472417
  • c04_referencelist : The list of journals cited in the paper 7472417 and the year of publication of the cited paper
  • year: 1995

'Title_abs_sample' :

  • PMID: 7472417
  • ArticleTitle : The title of the article 7472417
  • a04_abstract : The abstract of the article 7472417
  • year: 1995

Files

authors_sample.zip

Files (1.6 GB)

Name Size Download all
md5:6cbdc004f32563e864564d4c0a6dae43
415.6 MB Preview Download
md5:406d98d58089a153cd63190c3665bb54
200.8 MB Preview Download
md5:6b54a676b3be9eb34378828fd45b56dc
156.6 MB Preview Download
md5:b96c14ced1a2666d1e6a76c8372c5ace
16.8 MB Preview Download
md5:99e72ed1f52b22889c628ae5031a486f
822.3 MB Preview Download

Additional details

References

  • Xu, J., Kim, S., Song, M., Jeong, M., Kim, D., Kang, J., Rousseau, J.F., Li, X., Xu, W., Torvik, V.I. and Bu, Y., 2020. Building a PubMed knowledge graph. Scientific data, 7(1), pp.1-15.