Assembling Biomedical Big Data

Abstract

This chapter examines the challenges involved in disseminating, integrating and analyzing large datasets collected within both clinical and research settings. I highlight the technical, ethical and epistemic concerns underlying attempts to portray and use big data as revolutionary tools for producing biomedical knowledge and related interventions. When bringing together data collected on human subjects with data collected from other organisms, significant differences in the experimental cultures of biologists and clinicians emerge, which if left unchallenged may compromise the quality and validity of large-scale, cross-species data integration. The study of data integration calls attention to the fragmented, localized and inherently translational nature of biomedical research, and the challenges underlying the assemblage and interpretation of big data in this domain.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 5 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.