Toward Open Computational Communication Science: A Practical Road Map for Reusable Data and Code.

Computational communication science (CCS) offers an opportunity to accelerate the scope and pace of discovery in communication research. This article argues that CCS will profit from adopting open science practices by fostering the reusability of data and code. We discuss the goals and challenges re...

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Publicado en:International Journal of Communication (19328036) Vol. 13; pp. 3935 - 3955
Autores principales: VAN ATTEVELDT, WOUTER, STRYCHARZ, JOANNA, TRILLING, DAMIAN, WELBERS, KASPER
Formato: Artículo
Publicado: University of Southern California, USC Annenberg Press 2019
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Toward Open Computational Communication Science: A Practical Road Map for Reusable Data and Code.
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          VAN ATTEVELDT, WOUTER
          STRYCHARZ, JOANNA
          TRILLING, DAMIAN
          WELBERS, KASPER
        affil:
          Vrije Universiteit Amsterdam, the Netherlands
          University of Amsterdam, the Netherlands
      su:
        Communication
        Workflow
        Tools
        Databases
        Reproducible research
        Computer software reusability
      sug:
        subj:
          Communication
          Industrial Design Services
          Hardware Stores
          Cutlery and hand tool manufacturing
          Saw Blade and Handtool Manufacturing
          Power-Driven Handtool Manufacturing
          Workflow
          Tools
          Databases
          Reproducible research
          Computer software reusability
      keyword:
        computational communication science
        open science
        reproducibility
        reusability
        workflow
        computational communication science
        open science
        reproducibility
        reusability
        workflow
      ab: Computational communication science (CCS) offers an opportunity to accelerate the scope and pace of discovery in communication research. This article argues that CCS will profit from adopting open science practices by fostering the reusability of data and code. We discuss the goals and challenges related to creating reusable data and code and offer practical guidance to individual researchers to achieve this. More specifically, we argue for integration of the research process into reusable workflows and recognition of tools and data as academic work. The challenges and road map are also critically discussed in terms of the additional burden they place on individual scholars, which culminates in a call to action for the field to support and incentivize the reusability of tools and data.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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