Video: Data-sharing in connectomics

At Harvard University, neuroscientist Jeff Lichtman and his team generate a lot of data that they share. How easy is it to share connectomic data? Not very.
Published in Protocols & Methods
Video: Data-sharing in connectomics

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Sharing can be easy but it's often difficult. That's true for data-sharing, too. 

I did a story for Nature Methods on data-sharing  called To share is to be a scientist. And I am producing some additional multimedia to share more of what I found out and heard.

The US National Institutes of Health is asking researchers to think about data-sharing earlier than many have been. Scientists must now include a plan on data-sharing with their grant submission. This new policy is not exactly being greeted with hurrays all around. 

Neuroscientist Jeff Lichtman at Harvard University, who is an interviewee in the above-mentioned piece along with many others, has 1,400 terabytes to share. And doing so is quite challenging.  As he phrases it: today's terabyte is last years gigabyte.  Datasets are getting larger, in his lab they are beginning to talk of data amounts in terms of exabytes.

He's optimistic about new ways that are emerging to share such datasets and the new types of skillsets and professions that will also come about in this area.  

But there's no way around the fact that data-sharing in connectomics is hard, he says. 

In my case we share a dataset that's 1400's electron micrographs that have been annotated. 

I know I am at one extreme end of this...I think a lot of people are struggling with the exact same issue. There is no norm for connectomic data. ...Connectomics is, compared to genomics, is in its infancy. 


Note: Yes indeed, data are not like pizza but the sharing concept translates. 

A photo of sliced pizza and many hands grabbing slices.

(FlairImages/Getty Images

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