Establishing the reliability of measures extracted from long-form recordings using LENA and the ACLEW pipeline

This repository contains the data and the code necessary to reproduce the results of the paper "Establishing the reliability of measures extracted from long-form recordings using LENA and the ACLEW pipeline".

Structure

This repository is structured as follows :

CODE: contains the code necessary to preprocess the and to replicate the analysis of the paper
DATA: contains the data which is used for the analyses
DATASETS: contains the data sets which are used in this paper. Access to the data sets is only necessary to replicate the content of DATA (i.e. compilation of whole the metrics, children age, etc.). If you are not a LAAC member of trusted member, you cannot have access to this data. For more information, contact Alejandrina Cristia.
OUTPUT: contains the derived data (ICCs) computed by the script all-analyses.R using the data found in DATA
plots: contains the plots shown in the paper

Data Access

Re-using the dataset

Requirements

You will first need to install the ChildProject package for Python (optional) as well as DataLad. Instructions to install these packages can be found here.

Configuring your SSH key on GIN

This step should only be done once:

Create an account on (GIN)[https://gin.g-node.org/] if you don't have one already
Copy your SSH public key to your clipboard (usually located in ~/.ssh/id_rsa.pub). If you don't have one, please create one following these instructions
In your browser, go to GIN > Your parameters > SSH keys
Click on the blue "Add a key" button, then paste the content of your public key in the Content field, and submit

Your key should now appear in your list of SSH keys - you can add as many as necessary.

Installing the dataset

The next step is to clone the dataset :

datalad install -r git@gin.g-node.org:/LAAC-LSCP/RELIVAL.git
cd RELIVAL

Getting data

You can get data from a dataset using the datalad get command, e.g.:

datalad get CODE/* # download scripts
datalad get DATA/* # download data

Or:

datalad get . # get everything

You can download many files in parallel using the -J or --jobs parameters:

datalad get . -J 4 # get everything, with 4 parallel transfers

For more help with using DataLad, please refer to our cheatsheet or DataLad's own cheatsheet. If this is not enough, check DataLad's documentation and Handbook.

Fetching updates

If you are notified of changes to the data, please retrieve them by issuing the following commands:

datalad update --merge
datalad get .

Removing the data

It is important that you delete the data once your project is complete. This can be done with datalad remove:

datalad remove -r path/to/your/dataset

README.md 3.3 KB 히스토리 Download