Content area

Abstract

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.

Details

Title
Integrating big data with KNIME as an alternative without programming code: an application to the PATSTAT patent database
Pages
31-61
Publication year
2025
Publication date
Jan 2025
Publisher
Springer Nature B.V.
ISSN
14355930
e-ISSN
14355949
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3174603772
Copyright
Copyright Springer Nature B.V. Jan 2025