Integrating big data with KNIME as an alternative without programming code: an application to the PATSTAT patent database

Accessing massive datasets can be challenging for users unfamiliar with programming codes. Combining Konstanz Information Miner (KNIME) and MySQL tools on standard configuration equipment allows for addressing this issue. This research proposal aims to present a methodology that describes the necess...

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Bibliographic Details
Published in:Journal of geographical systems Vol. 27; no. 1; pp. 31 - 61
Main Authors: Taques, Fernando H., Chasco, Coro, Taques, Flávio H.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2025
Springer Nature B.V
Subjects:
Artificial intelligence
Big Data
Climate change
Comparative analysis
Computer Appl. in Social and Behavioral Sciences
Configurations
Data analysis
Data base management systems
Data science
Datasets
Econometrics
Economics
Economics and Finance
Geographical Information Systems/Cartography
Innovations
Landscape/Regional and Urban Planning
Machine learning
Massive data points
Original Article
Patent applications
Regional/Spatial Science
Reproducibility
Social responsibility
Software
Structured Query Language-SQL
Trends
Urban Economics
C88
PATSTAT
EPO
MySQL
Patent
Big data
C80
KNIME
O30
ISSN:1435-5930, 1435-5949
Online Access:Get full text
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Summary:Accessing massive datasets can be challenging for users unfamiliar with programming codes. Combining Konstanz Information Miner (KNIME) and MySQL tools on standard configuration equipment allows for addressing this issue. This research proposal aims to present a methodology that describes the necessary configuration steps in both tools and the required manipulation in KNIME to transmit the information to the MySQL environment for further processing in a database management system (DBMS). In addition, we propose a procedure so that the use of this point-and-click software in research work can gain in reproducibility and, therefore, in credibility in the scientific community. To achieve this, we will use a big database regarding patent applications as a reference, the PATSTAT Global 2023, provided by the European Patent Office (EPO). As well known, patent data can be a valuable source for understanding innovation dynamics and technological trends, whether for studies on companies, sectors, nations or even regions, at aggregated and disaggregated levels.
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ISSN:1435-5930
1435-5949
DOI:10.1007/s10109-024-00445-0