Nodebox network visualization6/22/2023 ![]() The dataset can be downloaded from Github in a zip file to unzip here. ![]() Very very similar results can be achieved using Open Refine as described in Chapter 9 of this Manual. The dataset has been extensively cleaned in Vantage Point by separating out applicant and inventor names and then using fuzzy logic matching to clean up names. The dataset consists of 5884 patent documents containing the terms “drone or drones” in the full text deduplicated to individual families from the full publication set. However, network visualisation can be used to visualise a range of fields and relationships, such as inventors, key words, IPC and CPC codes, and citations among other options.įor this chapter we will use a dataset on drones from the Lens patent database. In this article we will focus on creating a simple network visualisation of the relationship between patent applicants (assignees). You can read the chapter in electronic book format here and find all the materials including presentations at the WIPO Analytics Github homepage. ![]() This article is now a chapter in the WIPO Manual on Open Source Patent Analytics. We have chosen to focus on Gephi because it is a good all round network visualisation tool that is quite easy to use and to learn. In addition, network visualisation packages are available for R and Python. Gephi is one of a growing number of free network analysis and visualisation tools with others including Cytoscape, Tulip, GraphViz, Pajek for Windows, and VOSviewer to name but a few. This article focuses on visualising patent data in networks using the open source software Gephi.
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