From cosmos to connectomes: The evolution of data-intensive science

Research output: Contribution to journalShort surveypeer-review

Abstract

The analysis of data requires computation: originally by hand and more recently by computers. Different models of computing are designed and optimized for different kinds of data. In data-intensive science, the scale and complexity of data exceeds the comfort zone of local data stores on scientific workstations. Thus, cloud computing emerges as the preeminent model, utilizing data centers and high-performance clusters, enabling remote users to access and query subsets of the data efficiently. We examine how data-intensive computational systems originally built for cosmology, the Sloan Digital Sky Survey (SDSS), are now being used in connectomics, at the Open Connectome Project. We list lessons learned and outline the top challenges we expect to face. Success in computational connectomics would drastically reduce the time between idea and discovery, as SDSS did in cosmology.

Original languageEnglish (US)
Pages (from-to)1249-1252
Number of pages4
JournalNeuron
Volume83
Issue number6
DOIs
StatePublished - 2014

ASJC Scopus subject areas

  • General Neuroscience

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