C++ library for storing scientific data in the NIX data model.

The NIX data model allows to store fully annotated scientific datasets, i.e. the data together with its metadata within the same container. Our aim is to achieve standardization by providing a common/generic data structure for a multitude of data types.

NIX emerged from the activities of the Electrophysiology Task Force of the INCF Datasharing Program (2010-2015). It is a registered research resource with the RRID:SCR_016196.

We have restructured our documentation and all information is available on the project pages on ReadTheDocs

Documentation — where to find which information?

Project documentation is split up into three parts:

1. General Introduction and tutorial: Visit the project pages on ReadTheDocs
2. Technical information: Please visit the Wiki.
3. API documentations.

Further project related information:

• We have assembled a set of tutorials and demos using the python library.

The NIX ecosystem

In this repository you find the C++ library for reading and writing NIX files.

Further libraries

• Native python library: nixpy
• Matlab: nix-mx
• Java: nix-java

IO class for the NEO data model for spike train data.

Tools

• Viewer for NIX data files nixView

Used by

• relacs is a software platform for closed-loop data acquisition, online analysis, and stimulus generation specifically designed for (but not limited to) electrophysiological recordings. Writes out NIX files if the nix c++-library is installed.
• IO class for the NEO data model for neurophysiology data.
• Output format for EEGBase

Citing

If you use NIX, it would be much appreciated if you would cite it in publications with its identifier RRID:SCR_016196 and/or the reference:

Stoewer A, Kellner CJ, Benda J, Wachtler T and Grewe J (2014). File format and library for neuroscience data and metadata. Front. Neuroinform. Conference Abstract: Neuroinformatics 2014. doi: 10.3389/conf.fninf.2014.18.00027

Referenced By

• Dragly et al (2018) doi:10.3389/fninf.2018.000169
• Papez et al (2017) doi:10.3389/fninf.2017.00024
• Grewe et al (2017) doi:10.1073/pnas.1615561114
• Vanek et al (2016) doi:10.1109/informatics.2015.7377849
• Rübel et al (2016) doi:10.3389/fninf.2016.00048
• Denker et al (2016) doi:10.1007/978-3-319-50862-7_5
• Teeters et al (2015) doi:10.1016/j.neuron.2015.10.025

Contact

The project is maintained by the German Neuroinformatics Node, G-Node. G-Node at GitHub, email.

If you experience problems using NIX feel free to join our IRC channel #gnode at FreeNode or write an email to dev@g-node.org. If you find a bug please report it using the project issue tracker.

License

This project is open source published under the BSD-3 license see license file for details.