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README.md

This repository was created from the larkum lab template v.1.1. Access new template, or additional information at https://gin.g-node.org/larkumlab/Main_template. Please use issues in that repository to give feedback or ask questions about the template.


This repository is a home for your project, modify it the way you need it to be, start with this readme file!.

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Vestibulum nec augue in mauris tincidunt semper sed et eros. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Mauris finibus ante ac tempus vulputate. Etiam diam eros, sodales id urna eget, egestas tincidunt augue. Nunc consequat dui id nunc tincidunt tristique. Curabitur ultricies tortor sed quam pellentesque commodo. Fusce cursus sem sit amet sapien convallis, non volutpat nibh ullamcorper.


All data and documents related to one project should find its place here. If any file related to the project is stored outside of this repository, please indicate links in this file.

Here are some additional information about this version of the template, you are welcome to erase it to facilitate reading.


Template v.1.1:

  • 10_rawdata folder will be published upon publication, with or independently of the code folder.
  • 90_sharedfolder is meant for any file you want to share with the rest of the lab, so it is not shared outside the lab.

FAQ

What are derived and raw data?

In theory, data that can be derived from another dataset during the analysis is called derived data.In practice here, raw data is what will be stored long term, derived data will be trashed once the paper is published and we need the room. Because it becomes more costly to store the data (> 10 years) than to reproduce it, derived data are normally not stored. Note that if the derived data is small but the computing time to produce it is large (for example with video analysis producing a spreadsheet file), it is advised to put that dataset in the 10_rawdata folder.

Strickly speaking, raw data can be analog (notes on paper for instance), but qhat we call raw data here is the first digital version of the data you collected (in theory it can be picture of personal notes, stricly speaking it should be called primary data). It is good practice to document data provenance in order to be able to get back to the raw data (especially if it is not digital), if anything has to be changed in the analysis.

I am not using code ?

please then describe your analysis using words. The point is that the analysis can be performed again, by somebody else than yourself. That information would be better suited in the 40_notebook folder.

What is this author list below ?

This is a draft metadata to be used to publish datasets or software directly from GIN. It is created from the datacite.yml file, that you can modify.

This is actually meant to become a contributor list, i.e. not all people will become authors of the paper/dataset, some of the people listed here will end up in the aknowledgement part of the paper and you are free to erase names in the datacite.yml file.

datacite.yml
Title Example Title
Authors Sehara,Keisuke;Institut für Biologie, Neurocure Center for Excellence, Chariteplatz 1 / Virchowweg 6, Charité Universitätsmedizin Berlin & Humboldt Universität, Berlin, 10117 Germany.;ORCID:0000-0003-4368-8143
Larkum,Matthew E.;Institut für Biologie, Neurocure Center for Excellence, Chariteplatz 1 / Virchowweg 6, Charité Universitätsmedizin Berlin & Humboldt Universität, Berlin, 10117 Germany.;ORCID:0000-0001-9799-2656
Colomb,Julien;Institut für Biologie, Virchowweg 6, Humboldt Universität, Berlin, 10117 Germany.;ORCID:0000-0002-3127-5520
Description Example description that can contain linebreaks but has to maintain indentation.
License Creative Commons CC0 1.0 Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/)
References PublicationName1 [doi:10.xxx/zzzz] (IsSupplementTo)
PublicationName2 [arxiv:mmmm.nnnn] (IsSupplementTo)
PublicationName3 [pmid:nnnnnnnn] (IsReferencedBy)
Funding DFG, DFG.2112280105
DFG, DFG.LA 3442/3-1
DFG, DFG.LA 3442/5-1
DFG, DFG.327654276
EU, EU.670118
EU, EU.720270
Einstein Stiftung
Keywords Neuroscience
Electrophysiology
Resource Type Dataset