[Neuroinfo] Community feedback requested: the Neo object model

[INCF]

*Call for community feedback on the Neo object model for electrophysiology
and optophysiology data - open until August 14, 2022*

INCF is taking a leading role in endorsing and promoting standards and best
practices (SBPs) for global neuroscience
<https://link.springer.com/article/10.1007/s12021-020-09509-0>, as part of
our mission to promote data reuse and reproducibility in brain research.
SBP’s are nominated by the community and reviewed by the INCF SBP Committee
according to our criteria
<https://incf.org/incf-standards-review-criteria-v20> for a FAIR community
standard. If they meet our criteria, we put them up for 60 days of
community review to gauge the level of user support and to identify
possibilities for improvement and potential weaknesses.

For the next 60 days (Closing date:  August 14, 2022), we are seeking
community feedback on whether we should endorse the Neo object model
<https://www.incf.org/sbp/neo> as a standard.

Neo <https://www.incf.org/sbp/neo> is an object model for handling
electrophysiology data in multiple formats. It is suitable for representing
data acquired from electroencephalographic, intracellular, or extracellular
recordings, or generated from simulations. Neo has been implemented as a
Python package for working with electrophysiology data, together with
support for reading a wide range of neurophysiology file formats (including
Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, Igor Pro),
and support for writing to a subset of these formats plus non-proprietary
formats including Kwik and HDF5.

Should Neo be endorsed as a standard? Comments open until Aug 14:
f1000research.com/documents/11-658

Read more about Neo:
Project page <https://neuralensemble.org/neo/>
Documentation <https://neo.readthedocs.io/en/stable/>
Github <https://github.com/NeuralEnsemble/python-neo>
Paper <https://www.frontiersin.org/articles/10.3389/fninf.2014.00010/full>
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