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.

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Published
2024-10-28
DOI
https://doi.org/10.1109/conisoft63288.2024.00049
Primary Topic
Data Mining Algorithms and Applications
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article
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article

Transforming Semi-Structured Data into Structured Data by Using R

Rosa María Cantón Croda, Damián Emilio Gibaja Romero
Data Mining Algorithms and Applications
article

Transforming Semi-Structured Data into Structured Data by Using R

Rosa María Cantón Croda, Damián Emilio Gibaja Romero
article en

Abstract

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.

Universidad Popular Autónoma del Estado de Puebla (MX)
Openalex Percentile: Top 63%
Data Mining Algorithms and Applications
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