Data publications correlate with citation impact

Leitner, Florian and Bielza Lozoya, María Concepción and Hill, Sean L. and Larrañaga Múgica, Pedro María (2016). Data publications correlate with citation impact. "Frontiers in Neuroscience", v. 10 ; pp.. ISSN 1662-453X. https://doi.org/10.3389/fnins.2016.00419.

Description

Title: Data publications correlate with citation impact
Author/s:
  • Leitner, Florian
  • Bielza Lozoya, María Concepción
  • Hill, Sean L.
  • Larrañaga Múgica, Pedro María
Item Type: Article
Título de Revista/Publicación: Frontiers in Neuroscience
Date: September 2016
ISSN: 1662-453X
Volume: 10
Subjects:
Freetext Keywords: Data article citation index;DAC-index;Citations;Data sharing;open data;Data publications
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (465kB) | Preview

Abstract

Neuroscience and molecular biology have been generating large atasets over the past years that are reshaping how research is being conducted.In their wake, open data sharing has been singled out as a major challenge for the future of research. We conducted a comparative study of citations of data publications in both fields, showing that the average publication tagged with a data-related term by the NCBI MeSH(MedicalSubjectHeadings) curators achieves a significantly larger citation impact than the average in either field. We introduce a new metric, the data article citation index(DAC-index), to identify the most prolific authors among those data-related publications.The study is fully reproducible from an executable Rmd(RMarkdown)script to gether with all the citation datasets. We hope these results can encourage authors to more openly publish their data.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainC080020-09UnspecifiedUnspecifiedCajal Blue Brain
Government of SpainTIN2013-41592-PUnspecifiedUnspecifiedAprendizaje de redes bayesianas con variables sin y con direccionalidad para descubrimiento de asociaciones, predicción multirespuesta y clustering
Madrid Regional GovernmentS2013/ICE-2845CASI – CAMUnspecifiedConceptos y aplicaciones de los sistemas inteligentes
Horizon 2020720270HBP SGA1UnspecifiedHuman Brain Project Specific Grant Agreement 1

More information

Item ID: 46291
DC Identifier: http://oa.upm.es/46291/
OAI Identifier: oai:oa.upm.es:46291
DOI: 10.3389/fnins.2016.00419
Official URL: https://www.frontiersin.org/articles/10.3389/fnins.2016.00419/full
Deposited by: Memoria Investigacion
Deposited on: 06 Oct 2017 10:26
Last Modified: 22 Mar 2019 15:25
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM