[Neuroimaging] Planning for data formats - upcoming journal club

Satrajit Ghosh satra at mit.edu
Tue Nov 9 11:32:28 EST 2021


thank you matthew. happy to use any doc.

in the meantime a quick few pointers here: zarr, xarray, fsspec, intake
(all of these on the python side). let's also keep in mind compression and
chunking, two things the asdf model explicitly decided not to address. and
hdf5 now has serializable remote access on s3 stores both natively in the
library and through fsspec.

cheers,

satra

On Tue, Nov 9, 2021 at 11:21 AM Matthew Brett <matthew.brett at gmail.com>
wrote:

> Hi,
>
> On Tue, Nov 9, 2021 at 4:12 PM Satrajit Ghosh <satra at mit.edu> wrote:
> >
> > hi matthew,
> >
> > that paper is a great place to start. is there a document that you have
> where we can add thoughts/pointers to things that have been developed or
> reevaluated between 2015 and now ?
>
> I haven't got that far yet.  Anderson - I wonder whether your doc is
> good place for that?  Or do we need another one, less focused on HDF5?
>
> > quick clarification: is the scope of the discussion limited to certain
> types of data (e.g, MRI, transforms - i think this was in the czi proposal)
> or broadly speaking all things neuroimaging (e.g.
> MEG/EEG/Microscopy/Genetics/Surfaces) or even more general (e.g. nd-arrays,
> trees, graphs )?
>
> Certainly surfaces - these are on the CZI proposal - but I was - at
> the moment - thinking of MRI / CT / PET / transforms.  I haven't
> checked out the BIDS spec in detail - but I had naively imagined
> something that would be compatible with that, and cover the same sort
> of ground - if that proves interesting and necessary.
>
> For example - I could imagine a version of the nice YaML / binary ASDF
> format for neuroimaging data, that would have the advantage of being
> easily human-readable, being a single file to make copying and sharing
> easier, and allowing formal validation against a JSON schema.  But
> that's really way ahead of where I am now, personally - I've got lots
> of reading and listening to do.
>
> Cheers,
>
> Matthew
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