NDLI: GIS analysis of U.S. patent data: examining local innovation patterns

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GIS analysis of U.S. patent data: examining local innovation patterns

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GIS analysis of U.S. patent data: examining local innovation patterns

Content Provider	ACM Digital Library
Author	Moore, Jon Cui, Qian
Abstract	Current patent data in the United States provides limited spatial analysis capabilities within GIS applications. Most U.S. government data sources assign Federal Information Processing System (FIPS) codes or postal zip codes which facilitate GIS data input. However, neither the U.S. Patent and Trademark Office nor the National Bureau of Economic Research assign location codes, or geocodes, in patent records or patent applicant data. Instead, patent records contain postal town or city place-names provided along with U.S. state locations. Place-names may not be unique within certain states and data from large cities can only be attributed over a wide area. This has resulted in most patent research to be analyzed only at the state scale of analysis. This paper presents a method for data structures and geocoding that allows for geographical analysis of patents at the local (town, city and/or county) scale. This method is applied for data in Ohio from 2002 to 2006---the five most recent years of available data. The results show significant variability of data at the local scale. This variability is shown in terms of total patents, patenting by economic sector and for patent data standardized for the per capita labor force. The results also show the predominance of general manufacturing patents across the state, by comparison to specialized sectors. The results also illustrate two distinct innovation regions, along the I-75 corridor and in Northeast Ohio.
Starting Page	1
Ending Page	6
Page Count	6
File Format	PDF
ISBN	9781450306812
DOI	10.1145/1999320.1999339
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-05-23
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Gis Patents Innovation Ohio Business intelligence
Content Type	Text
Resource Type	Article

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