A Theoretical Framework for the Sociology of Data Science Practice in Nigeria’s Emerging Tech Ecosystem

The social and organisational dimensions of how data science is practised in Nigeria's technology ecosystem, including who does it, under what institutional conditions, and with what assumptions about knowledge and objectivity, have not been theorised, creating a gap in our understanding of the sociological foundations of Nigerian data science. This study developed an original theoretical framework for the sociology of data science practice in Nigeria's emerging tech ecosystem. A sociological theory-building methodology was employed, drawing on systematic review of science and technology studies and data science sociology literature (56 publications from 2018 to 2024), ethnographic observation at data science meetups and workplaces in Lagos and Abuja over six months, semi-structured interviews with 60 Nigerian data scientists, team leaders, and technology executives, and expert validation. Ethnographic and interview analysis identified Nigeria-specific sociological dimensions of data science practice not captured in existing sociological frameworks: the code-switching practitioner (moving between Western professional norms and Nigerian institutional realities), the digital diaspora influence (how Nigerian data scientists trained abroad shape local practice), and the infrastructure workaround culture (creative adaptation to data and compute scarcity). The original Nigerian Data Science Practice Sociology Framework proposes four analytical dimensions: practitioner identity formation, community of practice structure, knowledge production norms, and institutional embedding. Each dimension includes sociological constructs and empirical indicators. Expert review by 18 STS and data science studies scholars confirmed the framework's original sociological contribution.

Keywords: sociology of data science, Nigeria tech ecosystem, STS, practitioner identity, data science practice