Cloud-based Automatic Configuration and Disaster Recovery of Communication Systems Applied in Engineering Training — (Supplementary Material)

The supplementary dataset accompanying this study (10.3390/electronics13214203) provides resources to replicate the analysis of user evaluations and performance metrics for the DRACSC system. It includes structured CSV and XLS files containing raw and processed data from opinion surveys (Q1–Q22), grouped by thematic areas such as knowledge, motivation, usability and feasibility. Additionally, the dataset provides Python scripts (.py) to compute the Factorial Correspondence Analysis (FCA) and generate visualizations of relationships between user groups (students, teachers, professionals) and questionnaire items. The scripts automate data preprocessing, dimensionality reduction and plotting of symmetric maps, ensuring reproducibility of the statistical analysis. Together, these resources enable advanced exploration of correlations, variance components and behavioral patterns in ICT training environments. No other data related to the DRACSC internal algorithms is included due to intellectual property protection under patent WO/2016/055682.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-26
DOI
https://doi.org/10.5281/zenodo.17980265
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

Cloud-based Automatic Configuration and Disaster Recovery of Communication Systems Applied in Engineering Training — (Supplementary Material)

Tomás de J. Mateo Sanguino, Juan Diego Morillo Reina
Zenodo (CERN European Organization for Nuclear Research)
Digital Transformation in Industry
article

Cloud-based Automatic Configuration and Disaster Recovery of Communication Systems Applied in Engineering Training — (Supplementary Material)

Tomás de J. Mateo Sanguino, Juan Diego Morillo Reina
article en

Abstract

The supplementary dataset accompanying this study (10.3390/electronics13214203) provides resources to replicate the analysis of user evaluations and performance metrics for the DRACSC system. It includes structured CSV and XLS files containing raw and processed data from opinion surveys (Q1–Q22), grouped by thematic areas such as knowledge, motivation, usability and feasibility. Additionally, the dataset provides Python scripts (.py) to compute the Factorial Correspondence Analysis (FCA) and generate visualizations of relationships between user groups (students, teachers, professionals) and questionnaire items. The scripts automate data preprocessing, dimensionality reduction and plotting of symmetric maps, ensuring reproducibility of the statistical analysis. Together, these resources enable advanced exploration of correlations, variance components and behavioral patterns in ICT training environments. No other data related to the DRACSC internal algorithms is included due to intellectual property protection under patent WO/2016/055682.

Zenodo (CERN European Organization for Nuclear Research)
Universidad de Huelva (ES)
Climate action
Openalex Percentile: Top 44%
Digital Transformation in Industry
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