PATTERNS IN AWARD WINNING DATA STORYTELLING Story Types, Enabling Tools and Competences: Story Types, Enabling Tools and Competences

ADEGBOYEGA KOLAWOLE OJO

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

101 Citations (Scopus)

Abstract

Data storytelling is rapidly gaining prominence as a characteristic activity of digital journalism with significant adoption by small and large media houses. While a handful of previous studies have examined what characterises aspects of data storytelling like narratives and visualisation or analysis based on single cases, we are yet to see a systematic effort to harness these available resources to gain better insight into what characterises good data stories and how these are created. This study analysed 44 cases of outstanding data storytelling practices comprising winning entries of the Global Editors Networks Data Journalism Award from 2013 to 2016 to bridge this knowledge gap. Based on a conceptual model we developed, we uniformly characterised each of the 44 cases and then proceeded to determine types of these stories and the nature of technologies employed in creating them. Our findings refine the traditional typology of data stories from the journalistic perspective and also identify core technologies and tools that appear central to good data journalism practice. We also discuss our findings in relations to the recently published 2017 winning entries. Our results have significant implications for the required competencies for data journalists in contemporary and future newsrooms.
Original languageEnglish (Ireland)
Pages (from-to)693-718
Number of pages26
JournalDIGITAL JOURNALISM
Volume6
Issue number6
DOIs
Publication statusPublished - 1 Jan 2018

Keywords

  • Global Editor Network
  • data journalism skills
  • data journalism tools
  • data story
  • data storytelling types
  • data-driven journalism

Authors (Note for portal: view the doc link for the full list of authors)

  • Authors
  • Ojo, A,Heravi, B
  • Ojo, A.,Heravi, B.

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