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Article ID: CBB599481425

A Feeling for the Algorithm: Working Knowledge and Big Data in Biology (2017)

Osiris: A Research Journal Devoted to the History of Science and Its Cultural Influences
Volume: 32
Issue: 1
Pages: 151-174

DOI: 10.1086/693516

URI: https://www.journals.uchicago.edu/doi/abs/10.1086/693516

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Human-machine interaction Algorithms Genetics Databases Neural networks in biology; nerve net Biomedicine Big data 21st century 20th century, late

The term “Big Data” may serve as a useful marker for particular kinds of questions, practices, and relationships for collecting and using data. Some of the ways of talking about Big Data suggest that there might be something, if not entirely new, then at least importantly different at work in Big Data practices and problem-solving approaches. By using three examples taken from the biomedical sciences—artificial neural networks, the construction of reference genomes, and the usage of the Ensembl database—this essay shows how Big Data practices cannot be understood as mere scaling up of pen-and-paper methods but constitute qualitatively different kinds of knowledge-making practices. These practices are characterized particularly by types of human-computer interaction that are labeled “a feeling for the algorithm.”

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Article Bruno J. Strasser; Paul N. Edwards (2017) Big Data Is the Answer … But What Is the Question?. Osiris: A Research Journal Devoted to the History of Science and Its Cultural Influences (pp. 328-345). unapi

Article Elena Aronova; Christine von Oertzen; David Sepkoski (2017) Introduction: Historicizing Big Data. Osiris: A Research Journal Devoted to the History of Science and Its Cultural Influences (pp. 1-17). unapi

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