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Software . 2025
Data sources: ZENODO
ZENODO
Software . 2025
Data sources: Datacite
ZENODO
Software . 2025
Data sources: Datacite
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Codebook Generator App

Générateur de dictionnaires de données
Authors: Digital Research Alliance of Canada; Manrique-Castano, Daniel;

Codebook Generator App

Abstract

Le Générateur de dictionnaires de données est une application web open source conçue pour aider les chercheurs et gestionnaires de données à créer des dictionnaires de données (codebooks) structurés et normalisés à partir de jeux de données tabulaires (CSV, TSV, Excel). Elle propose une interface interactive accessible via un navigateur, qui permet d'extraire automatiquement les noms de variables, de détecter les types, d’identifier les valeurs manquantes et de résumer les plages de valeurs ou les niveaux de facteurs. Les utilisateurs peuvent ensuite annoter les variables à l’aide de libellés compréhensibles et d’unités, favorisant ainsi la transparence, la réutilisation et l’interopérabilité des données scientifiques. L’application est développée en R à l’aide du framework Shiny et fonctionne entièrement côté client lorsqu’elle est déployée avec ShinyLive, garantissant la confidentialité des données — aucune donnée n’est stockée ni transmise pendant l’utilisation. L’interface respecte les bonnes pratiques en matière de durabilité des logiciels de recherche. Son développement s’inspire des principes FAIR et vise à soutenir des pratiques de recherche reproductibles. La documentation, les instructions d'utilisation et les lignes directrices pour les contributions sont disponibles dans le dépôt Git. Un tutoriel de démarrage rapide et une présentation de l’architecture logicielle y sont également proposés. Dépôt GitHub : https://github.com/Alliance-RDM-GDR/RDM_Codebook_AppEssayer en ligne : https://alliance-rdm-gdr.github.io/RDM_Codebook_App/

The Codebook Generator is an open-source web application designed to help researchers and data managers create structured and standardized codebooks for tabular datasets in formats such as CSV, TSV, and Excel. It provides an interactive, browser-based interface to automatically extract variable names, detect types, identify missing values, and summarize value ranges or factor levels. Researchers can then annotate variables with human-readable labels and units, facilitating transparency, reuse, and interoperability of scientific data. This app was developed in R using the Shiny framework and is fully client-side when deployed via ShinyLive, ensuring data privacy—no data is stored or transmitted during use. The app supports best practices for research software sustainability. Its design was inspired by the FAIR principles and aims to support reproducible research workflows. Documentation, usage instructions, and contribution guidelines are included in the project repository. A quick-start tutorial and architecture overview are also available to guide new users and developers. Repository: https://github.com/Alliance-RDM-GDR/RDM_Codebook_AppTry it online: https://alliance-rdm-gdr.github.io/RDM_Codebook_App/

Related Organizations
Keywords

codebook, data sharing, open science, research data management

  • BIP!
    Impact byBIP!
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average