NIXIO Python library documentation¶

The NIXIO module is the native python re-implementation of the NIX C++ library for 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. See the wiki or the introduction for more information.

The current implementations store the actual data using the HDF5 file format as a storage backend.

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.

Introduction¶

We have assembled introductory material that illustrates using nix. The tutorials contain several code examples. The use_cases explain in more detail how nix is used in real world situations.

Support¶

If you need help, want to get in touch, or have any other request these are your options.

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¶

Sinz et al. (2020) doi:10.1152/jn.00615.2019
Buccino et al. (2019) doi:10.1101/796599
Sprenger et al. (2019) doi:10.3389/fninf.2019.00062
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

Introduction

Tutorials

Tutorials