Data Science, Meaning, and Diversity - Speaking at CorrelAidX Stuttgart
Creators: name: Kherroubi Garcia, Ismael
Publisher: name: Zenodo
Year: 2021
Subjects: epistemology; data science; feminism

description: The attributes of interpretation, materialisation, context and documentation are proposed as necessary conditions for data to be meaningful and useful for a data science that seeks to generate actionable knowledge. However, these attributes elicit the challenges of multidisciplinary, abstraction and decontextualisation in data science. I suggest that epistemic humility and diversity – as prescribed by Standpoint Theory – as providing a framework to do data science better. The slides contain speaker notes and are best rendered on a Mac because of the "Chalkduster" font used.
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