Reliance on Science in Patenting

This contains citations from the front pages of worldwide patents to articles in he Microsoft Academic Graph (MAG) from 1800-2018. Questions &amp; feedback to [e-mail]<em>.</em> <strong>If you use the data, please cite these two papers:</strong> <em>for the dataset of citations: </em>Marx, Matt and Aaron Fuegi, "Reliance on Science: Worldwide Front-Page Patent Citations to Scientific Articles" (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3331686). <em>for the articles:</em> Sinha, A, et al. 2015. Overview of Microsoft Academic Service (MAS) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW ’15 Companion). ACM, New York, NY, USA, 243-246. The files below are described in <strong>_datadescription.pdf</strong> but here is a brief summary: _<strong>pcs.tsv</strong>, contains the patent citations to science. Fields are tab-separated. Each citation to science has the patent number, MAG ID, applicant/examiner indicator, and a confidence score (1-10). <strong>_pcs_pubmed.tsv</strong>, is a PubMed-specific match currently limited to USPTO patents. <strong>_pcs_bodytextbeta.tsv</strong> is a <em>preliminary</em> release also containing citations from the body text of USPTO patents since 1836. This adds a field indicating whether the citation appeared on the front page, in the body text, or in both. The remaining files redistribute the 1/1/2019 release of the Microsoft Academic Graph, carving up the original files into smaller, variable-specific files. There are also some extensions including journal impact factor and high-level technical classifications. Source code is available at https://github.com/mattmarx/reliance_on_science.