This repository contains the data and analysis workflow related to the study:
"Patent data-driven analysis of literature associations with changing innovation trends."
Adrian Sven Geissler, Jan Gorodkin, and Stefan Ernst Seemann.
Frontiers in Research Metrics and Analytics, 2024.
https://www.frontiersin.org/journals/research-metrics-and-analytics/articles/10.3389/frma.2024.1432673/
The analysis relates to 2 datasets of patent-literature associations downlaoded from the Lens platform (https://www.lens.org/). The 2 datasets relate to all patents that match the search terms "CRISPR" (downloaded July 6, 2023) and "cyanobacteria" (downloaded July 3, 2023).
The analysis matches all patents to IPC terms (international patent classification). After identifying IPC terms with trend changes in the number of patents over time, an over-representation test identifyies which literature is associated with the respective patents (and thus might be of interest in explaining the change in innovation trend).