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Episode #17: Big Data and Good Science
FromBioScience Talks
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Length:
35 minutes
Released:
Oct 13, 2016
Format:
Podcast episode
Description
Scientists have long debated the best methods to achieve sound findings. In recent decades, hypothesis-driven frameworks have been enshrined in textbooks and school courses, with iterative and inductive approaches often taking a back seat. However, the advent of big data poses a challenge to the established dogma, as large data sets often require broad collaborations and make traditional hypothesis-driven approaches less tractable. For this episode of BioScience Talks, we spoke with Michigan State University professors Kendra Cheruvelil, Georgina Montgomery, Kevin Elliott, and Patricia Soranno. Their interdisciplinary work highlights the changing scientific landscape, in which large data sets and new computational methods encourage a more iterative approach to science. Read the article discussed on the show. Subscribe on iTunes. Subscribe on Stitcher.
Released:
Oct 13, 2016
Format:
Podcast episode
Titles in the series (100)
Preview of BioScience Talks Episode 1: This episode previews BioScience Talks' upcoming first episode on coupled human and natural systems, to be released on 10 June. Stay tuned! by BioScience Talks