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A database linking Chinese patents to China’s census firms
To meet researchers’ increasing interest in the fast growing innovation activities taking place in China, we match patents filed with China’s State Intellectual Property Office to firms covered in China’s Census. China has experienced a strong growth in patent filings over the past two decades, and...
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Published in: | Scientific data 2018-03, Vol.5 (1), p.180042-180042, Article 180042 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | To meet researchers’ increasing interest in the fast growing innovation activities taking place in China, we match patents filed with China’s State Intellectual Property Office to firms covered in China’s Census. China has experienced a strong growth in patent filings over the past two decades, and has since 2011 become the world’s top patent filing country. China’s Census database covers about one million unique manufacturing firms from 1998–2009, representing the broad Chinese economy. We design data parsing and pre-processing routines to clean and stem firm and assignee names, create a matching algorithm that fits with our data and maintains a balance between matching accuracy and workload of manual check, and implement a systematic manual check process to filter out false positives generated from computerized matching. Our project generates 1,113,588 matches for the Census firms, among which 849,647 patents are uniquely matched. By creating the patent-firm linked dataset, we hope to reduce duplicative effort and encourage more research to better understand China’s fast changing innovation landscape.
Design Type(s)
data integration objective • natural language processing objective • text processing and analysis objective
Measurement Type(s)
patent
Technology Type(s)
digital curation
Factor Type(s)
Sample Characteristic(s)
China
Machine-accessible metadata file describing the reported data
(ISA-Tab format) |
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ISSN: | 2052-4463 2052-4463 |
DOI: | 10.1038/sdata.2018.42 |