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23 03, 2020

Archiv and Ablage


Archiv and Ablage

[Written by Johanna on 2019/06/20]

The title will probably be the key word that appears in the wiki and is thus directly linked to your entry.

Table of content

  1. What is it for?
    • Ablage
    • Archiv
  2. How do I get access?
    • Ablage
    • Archiv
  3. How do I store my data there?
    • Ablage
    • Archiv
  4. Links

What is it for?

The Ablage and Archiv can be used to store your data. There are a few differences between the two:


If you want to back-up data from a running project or want to save files/data your currently working with on a Charité-Server, you can use this folder. The Ablage has space for 8TB.


Additionally to the Datenablage, we now have access to the Archiv (10TB). The Archiv can be used for data which won’t be modified anymore. Everybody should think about what they can put in the Archiv to save space in the Datenablage, e.g. already finished projects.

How do I get access?


To store data in the Ablage, you need to get permission by the Charité IT.

You must fill out this form: https://intranet.charite.de/fileadmin/user_upload/microsites/gb/it/sys/Beantragung-Rechte.pdf

Johanna/Leonie can help you if you should have questions.

You then find the folder DATEN here:


– AG




Because we seriously cannot modify the data once it is uploaded in the Archiv, we have to be very careful what we put there. Everybody who got granted access to the Datenablage is also able to read the Archiv. However, only Maron and Johanna/Leonie have the possibility to upload data.

How do I store my data there?


The folder structure is the following: \NAME\PROJECT

Please keep in mind that the space is limited to 8TB for the whole lab. To keep track of the Datenablage, Carsten made this google doc:


Please put all the relevant information concerning the data you want to store in this spreadsheet.


If you want to store data in the Archiv

(1) put your data in the folder ‘ready_for_archiv’ in the Datenablage

(2) Write a mail to Maron and/or Johanna/Leonie and we will move the data to the Archiv



Archiv and Ablage2020-04-01T10:24:30+02:00
23 03, 2020



HOW TO: GitHub for Version Control

[Written by Graham Cooper on 2019/15/01]

Table of content

  1. Version Control in GitHub
  2. Set up Git and GitHub
  3. Git Commands
  4. Links
  5. Literature

Version Control in GitHub

Reproducibility ensures that anyone (including you in 6 months’ time!) can take your data and get the same results and tables that you originally found/generated. Problems with reproducibility (and how to overcome these) have been widely discussed in recent years, particularly in the behavioral sciences. One major obstacle standing in the way of reproducibility in research is good curation of data, i.e. storing everything in a sensible place, keeping track of changes in files by various collaborators. This is a particular challenge for us as researchers as (generally) we have been taught how to collect and analyze data to a high level of skill but have received next to no training in how to curate that data once it exists. Git (and GitHub) is one popular version control system that enables such data curation and is widely used in the field of software engineering, where the skills of data science/data management are taught to a gold standard. Using Git and GitHub, you have one space where all your relevant documents can be stored. Every version of your documents is saved so you can easily go back and check previous versions without needing to search through endless files names “manuscript_draft_version_16_FINAL_draft_ACTUAL_FINAL_DRAFT.doc”, for example! It also makes collaboration easier as everyone can work on the same document at once and merge versions, while keeping track of who did what. At the end of the project it also facilitates sharing of data and code as you can make a private repository public and add a link that everyone can access.

Currently GitHub allow users to have unlimited private repositories!

See Vuorre & Corley (2018) for a more detailed tutorial on Git and GitHub including how to set it up. A link to the online pdf is available in the links section.

Git Commands

Below is a list of common commands for Git and what they are used for.

git init

Initializes an empty git repository

git status

Shows all changes made since last “commit”

git add

Adds changes to the file to be committed

git commit -m “added file”

Commit all changes (signify that these changes should be included in the document). The text after the -m flag is the commit message that describes the changes you made



  1. Vuorre, M. & Curley, J. P. (2018) Curating Research Assets: A Tutorial on the Git Version Control System. Advances in Methods and Practices in Psychological Science, 1(2).
23 03, 2020

WIKI Open Science Framework


Open Science Framework

The Open Science Framework is an online platform (https://osf.io/) for the advancement of open science and scientific collaboration. It originates from the 2013-founded Center for Open Science (https://cos.io/) which seeks to increase the integrity and reproducibility of scientific research. While the project started out with a focus on reproducibility of psychology studies, it is by now applicable to researchers of virtually any field who wish to increase the transparency of their work.

In light of the reproducibility crisis across many scientific fields, the importance of improving practices of scientific transparency is increasingly recognized. With respect to neuroscience, a highly recommendable read in this regard is Poldrack (2019) who highlights the necessity but also some challenges that come with adopting better reproducibility practices.

The Open Science Framework (OSF) is one such tool to enable improved reproducibility. Its functionality is constantly increasing but the web platform is at the heart of it. Here you organize your work into different projects, e.g.:

These projects may either be private or public. In private projects, only people with permission have access to it – for instance if you just want to share research content with other contributors in your project. In public projects, everyone can access the content via a link. As you create a new project, you can first work on it privately and then make it public as you submit your paper. You can also create a digital object identifier and your project is also citable and a great way to share data / code / supplementary material in a paper, e.g.

Krohn, S., & Ostwald, D. (2017, February 26). Computing Integrated Information. Retrieved from https://osf.io/hb4a5/.

Once you enter a project, this is what the platform looks like:

There is a Wiki to explain the content of the project (upper left) – which is recommendable to help the user navigate your content. You can also choose to license your content (upper left), and you can add different components to your project (cf. right column) to structure it into different subprojects. Perhaps most importantly, there is a “Files” section where you can upload content to an OSF-hosted server. This works neatly for code, result summaries, figures, etc., for example:

If you want to share some result summaries (such as a table or a text file), this is also good to include. For large raw data, there is usually a space limitation (although you can also get in contact with the support to ask for more space or how to best publish your particular data). For more sharing options, a nice feature is that you can now also embed external applications into the OSF. For instance, you may have some files on a Google Drive or owncloud, or you have some shared code in a git repository such as Bitbucket or Github. These and increasingly more applications (now also including citation managers) can be added to your OSF project, for example:

Finally, there are other related useful functionalities:

1) My Quick Files (see figure 1) is an easy drap-and-drop way to share files.

2) The OSF now hosts its own preprint server. https://osf.io/preprints/

3) The OSF now also features study preregistration, with demos, guidelines and public templates of how to use them. https://osf.io/prereg/


Poldrack RA. (2019). The Costs of Reproducibility. Neuron. 101(1):11-14. doi: 10.1016/j.neuron.2018.11.030.

WIKI Open Science Framework2020-04-01T10:24:23+02:00