Datafication Research (1994–2023): Three Decades of Evolving Methodology in Data Science.

This study maps the evolution of research themes on datafication, analyzing trends, key authors, interdisciplinary collaborations, and emerging topics from 1994 to 2023. The analysis reveals a notable increase in publication volume, particularly from 2014 onwards, reflecting advancements in digital...

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Publicado en:Topoi: An International Review of Philosophy Vol. 44; no. 4; pp. 1049 - 1071
Autor principal: Nwagwu, Williams Ezinwa
Formato: Artículo
Publicado: Springer Nature Oct2025
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Acceso en línea:Ver este registro en EBSCOhost
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        atl: Datafication Research (1994–2023): Three Decades of Evolving Methodology in Data Science.
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        au: Nwagwu, Williams Ezinwa
        affil:
          https://ror.org/03wx2rr30 Department of Data and Information Science, University of Ibadan, 6 Benue Rd, Ibadan, Nigeria
          https://ror.org/048cwvf49 Department of Information Science, University of South Africa, Pretoria, South Africa
      su:
        Data science
        Interdisciplinary research
        Digital technology
        Ethical problems
        Data management
        Research methodology
        Digital divide
      sug:
        subj:
          Data science
          Interdisciplinary research
          Digital technology
          Ethical problems
          Data management
          Research methodology
          Digital divide
      keyword:
        Artificial intelligence
        Datafication
        Datafication and social transformation
        Information and Computing Sciences Artificial Intelligence and Image Processing
        Methodology
        Visualisation
      ab: This study maps the evolution of research themes on datafication, analyzing trends, key authors, interdisciplinary collaborations, and emerging topics from 1994 to 2023. The analysis reveals a notable increase in publication volume, particularly from 2014 onwards, reflecting advancements in digital technologies and heightened interest in data-driven research. A significant surge occurred during the COVID-19 pandemic, with 26.10% of total publications in 2022 and 30.52% in 2023 alone. Thematic clusters identified through keyword mapping include Social Media and Privacy, Artificial Intelligence and Machine Learning, Human Dimensions, and Infrastructure and Trust, highlighting diverse research foci. Emerging discussions on data justice and inequality reflect growing attention to the ethical and socio-political implications of datafication. The study also examines the types of documents and subject areas, revealing the dominance of peer-reviewed journal articles (71.41%) and a strong representation of social sciences (46.93%), computer science (14.75%), and arts and humanities (11.57%). Interdisciplinary connections underscore the broad impact of datafication across technology, healthcare, education, and media studies. This research offers insights into the dynamic nature of datafication, pointing to the need for further interdisciplinary collaboration, especially in addressing societal and ethical concerns such as data governance and digital inequality. Future research directions should focus on the human dimensions of datafication, data literacy, and the development of robust data governance frameworks to mitigate potential inequalities and power imbalances in a rapidly data-driven world.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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