A reflective look at the epistemological context of data analytics
DOI:
https://doi.org/10.18634/sophiaj.21v.1i.1440Keywords:
data science, field of research, education and research, epistemologyAbstract
The modern abundance and prominence of data has led to the development of “data science” as a new field of research, along with a body of epistemological reflections on its foundations, methods, and consequences. This article is derived from the research exercise on the purposes of education where the analysis of knowledge provides a systematic dynamic and a critical review of important problems and open debates in the epistemology of analytics and data science, proposing a division of epistemology of data science in the following five aspects: Maximalistic and minimalist characterizations, descriptive taxonomies, the knowledge generated by data science, black box problems and science in a data-intensive paradigm, aspects that provide a reflective exercise against to understanding and addressing essential aspects of data interpretation and understanding hidden patterns in them, this being the challenge of analytics as such.References
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