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

Guardado en:
Publicado en:Journal of Geographical Systems vol. 27, no. 1 (Jan 2025), p. 31
Publicado:
Springer Nature B.V.
Materias:
Databases
Data base management systems
Big Data
Patent applications
Massive data points
Configurations
Tools
Innovations
Social responsibility
Machine learning
Software
Datasets
Artificial intelligence
Trends
Data analysis
Data science
Structured Query Language-SQL
Reproducibility
Climate change
Comparative analysis
Patents
Economic
Acceso en línea:Citation/Abstract
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Resumen: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.
ISSN:1435-5930
1435-5949
DOI:10.1007/s10109-024-00445-0
Fuente:ABI/INFORM Global