Of Schemes and Memes Blog

On the road at #SfN13 – Tackling the terabyte: how should research adapt to the era of big data?

If you’re attending the Society for Neuroscience meeting this year (#SfN13), join us for our panel discussion: ‘Tackling the terabyte: how should research adapt to the era of big data?

When: Monday, November 11, 6:30 – 8:30 p.m.

Where: Hilton San Diego Bayfront, 1 Park Blvd, San Diego, CA 92101  

Room: Sapphire 400


  • Noah Gray, Nature


  • Susanna-Assunta Sansone, Assoc Dir & PI at University of Oxford e-Research Centre; Honorary Academic Editor, Scientific Data
  • Mark Hahnel, Figshare
  • Kalyani  Narasimhan, Nature Neuroscience
  • Sean Hill, International Neuroinformatics Coordinating Facility (INCF)
  • Maryann Martone, University of California San Diego, UCSD (Neuroscience Information Framework)

Plus after the panel discussion join us for a networking event where our panellists will be joined by:

  • Brian Wandell (Stanford): fMRI data
  • Laura Colgin (U. Texas): Navigational behavior/neural spike data
  • Andrew Hires (USC): Microscope imaging/sensorimotor behavior data

Please tweet any questions for the panel using the hastag #SfN13data

Places are limited and only 150 delegates will be admitted.



Tackling the terabyte: how should research adapt to the era of big data?

It’s getting easier and easier to collect gigabytes of data, but many scientists lack the skills to use it or are trained in how to best organize it.

Computer models also produce very complex theoretical predictions, but how do you compare the outcome of a complex model with the original data?  How much duplicated data exists? What rights management is associated with data reuse? And should data that’s made available for reuse be peer-reviewed?

Managing such large volumes of data represents a fundamental change in how experimental science is done, is the research community prepared for this change?    How should we start to tackle this problem? Should universities have data specialists? And who would pay for them?  Aren’t we all busy enough already?

Other topics to consider:

  • Will journals act as depository for ‘Big Data’?
  • Neuroinformatics – integration/analysis of large-volume, high-dimensional & fine-grain experimental data (Neuroscience Database Gateway)
  • Where do we go with neurosci data – (driving policy, adding value to papers, author credit) ?
  • Mandate the sharing of information?
  • Should all research be peer reviewed – Blogs vs social media?
  • Using social networking to aid research (collaboration)
  • What should ‘journals’ (Independent v Society) be doing to facilitate / How can journals help?


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