Transforming Semi-Structured Data into Structured Data by Using R
The increasing use of digital platforms has boosted the generation of databases with heterogeneous data. So, Model Driven Engineering faces the challenge of developing efficient methodologies that deal with semi-structured data for their treatment and analysis. This paper applies the R language to develop a transformation chain that links models with different abstraction levels. Such a transformation also transforms semi-structured data into structured data, which allows us to facilitate the analysis of heterogeneous databases. In this sense, we show that the R language can be applied to solve software engineering problems since <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R$</tex> provides an environment that guarantees maintainability, reusability, and extensibility concerning the treatment of heterogeneous databases.
Authors
- Rosa María Cantón Croda (ORCID: https://orcid.org/0000-0002-5469-8964)
- Damián Emilio Gibaja Romero (ORCID: https://orcid.org/0000-0002-3536-4117)
Institutions
- Universidad Popular Autónoma del Estado de Puebla (MX)
Publication Details
- Published
- 2024-10-28
- DOI
- https://doi.org/10.1109/conisoft63288.2024.00049
- Primary Topic
- Data Mining Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00