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Principios FAIR de gestión de datos de investigación en ciencias de la salud

Authors: Eveline García-Espinosa; Adrián Alejandro Rojas-Concepción; Adrián Alejandro Vitón-Castillo; Carlos Oscar Lepez;

Principios FAIR de gestión de datos de investigación en ciencias de la salud

Abstract

Introducción: los datos abiertos para la validación y generalización de los resultados de investigación, así como el reciclaje de sets de datos constituye una sentida necesidad en la asistencia médica. Objetivo: describir los principios FAIR de gestión de datos de investigación. Método: se realizó una búsqueda de información en las bases de datos Scopus, SciELO, Redalyc y PubMed/MedLine mediante una fórmula con el uso combinado de términos y operadores booleanos. Se emplearon los términos “Datos abiertos”, “datos de investigación”, “FAIR”. Desarrollo: los datos abiertos representan un avance en las ciencias de la información, y en el campo de la salud han alcanzado progresos en la última década. No basta solo con producir y compartir datos, estos deben cumplir un conjunto de principios para su digitalización, reproducibilidad y reciclaje. Los FAIR buscan lograr sets de datos localizables, accesibles, interoperables y reutilizables, así como la eliminación de barreras culturales, socioeconómicas y técnicas. Su aplicación en las ciencias de la salud permite un mejor uso de los recursos al evitar la replicación de investigaciones con resultados negativos, concede la reutilización de datos y la generalización de resultados mediante la combinación de los mismos. Conclusiones: los principios FAIR buscan fortalecer la ciencia abierta, eliminar barreras, desarrollar infraestructuras, protocolos y políticas de datos. Su aplicación en las ciencias de la salud es de gran valor, por constituir una poderosa herramienta para mejorar las prácticas investigativas y asistenciales.

Keywords

science communication and dissemination; science, technology and innovation management in health system; information access

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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!
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