initial commit

.datalad/path

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+/scratch1/data/laac_data/polish-dataset

.datalad/procedures/setup.py

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+#!/usr/bin/env python3
+
+import sys
+import os
+import re
+
+import datalad.api
+from datalad.distribution.dataset import require_dataset
+
+import argparse
+
+parser = argparse.ArgumentParser(description='setup the dataset siblings')
+parser.add_argument('path', help = 'path')
+parser.add_argument('--confidential', help = 'setup access to confidential remote', action = 'store_true')
+parser.add_argument('--public', help = 'setup access to public remote', action = 'store_true')
+
+args = parser.parse_args()
+
+ds = require_dataset(
+    args.path,
+    check_installed = True,
+    purpose = 'configuration'
+)
+
+datalad.api.siblings(
+    name = 'origin',
+    dataset = ds,
+    action = 'configure',
+    annex_wanted = '(include=*) and (exclude=**/confidential/*)',
+    annex_required = '(include=*) and (exclude=**/confidential/*)'
+)
+
+url = datalad.api.siblings(name = 'origin', dataset = ds)[0]['url']
+confidential_url = os.path.splitext(url)[0] + '-confidential.git'
+public_url = os.path.splitext(url)[0] + '-public.git'
+
+if args.confidential:
+
+    datalad.api.siblings(
+        name = 'confidential',
+        dataset = ds,
+        action = 'add',
+        url = confidential_url
+    )
+
+    datalad.api.siblings(
+        name = 'confidential',
+        dataset = ds,
+        action = 'configure',
+        annex_wanted = 'include=**/confidential/*',
+        annex_required = 'include=**/confidential/*'
+    )
+    
+if args.public:
+
+    datalad.api.siblings(
+        name = 'public',
+        dataset = ds,
+        action = 'add',
+        url = public_url
+    )
+
+    datalad.api.siblings(
+        name = 'public',
+        dataset = ds,
+        action = 'configure',
+        annex_wanted = '(include=annotations/vtc/converted/* or include=annotations/vcm/converted/* or include=annotations/alice/converted/* or include=annotations/alice/output/converted/* or include=annotations/its/converted/*) and exclude=**/confidential/*',
+        annex_required = '(include=annotations/vtc/converted/* or include=annotations/vcm/converted/* or include=annotations/alice/converted/* or include=annotations/alice/output/converted/* or include=annotations/its/converted/*) and exclude=**/confidential/*'
+    )
+
+if args.public and args.confidential:
+    datalad.api.siblings(
+        name = 'origin',
+        dataset = ds,
+        action = 'configure',
+        publish_depends = ['confidential','public']
+    )
+elif args.public:
+    datalad.api.siblings(
+        name = 'origin',
+        dataset = ds,
+        action = 'configure',
+        publish_depends = 'public'
+    )
+elif args.confidential:
+    datalad.api.siblings(
+        name = 'origin',
+        dataset = ds,
+        action = 'configure',
+        publish_depends = 'confidential'
+    )
+    
+

.gitattributes

@@ -1,2 +1,7 @@
 * annex.backend=MD5E
 **/.git* annex.largefiles=nothing
+scripts/* annex.largefiles=nothing
+metadata/*.csv annex.largefiles=nothing
+recordings/* annex.largefiles=((mimeencoding=binary)and(largerthan=0))
+README.md annex.largefiles=nothing
+

README.md

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+# Dataset Name
+
+Suggested citation: XXX.
+
+## Data description
+
+### Data documentation
+
+The dataset is structured according to the ChildProject package standards detailed [here](https://childproject.readthedocs.io/en/latest/format.html).
+
+### Participants & recordings
+
+>Number of participants, general info on them.
+
+>Number of recordings, specificities.
+
+### Available annotations
+
+>What sort of annotations are presents. 
+
+**We strongly recommend the use of the `converted/` versions of the annotations, to avoid issues of time stamping and category assignment.**
+
+#### Automated annotations
+>keep relevant, add new ones if necessary
+
+- alice: automated counts of phonemes, syllables, and words done by [ALICE](https://github.com/orasanen/ALICE); all recordings have been analyzed with this system
+- its: automated analyses using the LENA software; only a small proportion of recordings (those gathered with a LENA device) have this annotation
+- vcm: automated analyses aimed at categorization the key child's vocalizations into: canonical, non-canonical, crying, and other (which includes both "junk" = not the child at all; and laughing, which occurred infrequently), done using [VCM](https://github.com/srvk/DiViMe/blob/master/docs/source/tool_doc.md#vcm); all recordings have been analyzed with this system
+- vtc: automated analyses that distinguish key child, other children, male adult, female adult, using [VTC](https://github.com/MarvinLvn/voice-type-classifier); all recordings have been analyzed with this system
+
+#### Manual annotations
+>explain what each set of manual annotation is and how it was produced
+>Example from tsimane2017:
+>- eaf_2021: A small number of recordings were selected for coding by two speech-and-language students unfamiliar with the language and the families recorded, who annotated randomly sampled 15-second sections, skipping any that failed to contain speech by male adults or other children, following [this coding manual](https://docs.google.com/document/d/19-EzpJNHT-pcagHm0-ZasAu2PzwT9j5lgz-SqC5zWTI/edit#heading=h.gt6kkkg2awdf), derived from the ACLEW Annotation Scheme, to do only segmentation.
+
+## Getting access to the data
+
+To gain access to the data, please email XXXX? or Homebank or ... ?
+
+
+## Re-using the dataset
+
+### Requirements
+
+You will first need to install the ChildProject package as well as DataLad. Instructions to install these packages can be found [here](https://childproject.readthedocs.io/en/latest/install.html).
+
+### Configuring your SSH key on GIN
+
+This step should only be done once for all.
+
+1. 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](https://docs.github.com/en/github/authenticating-to-github/generating-a-new-ssh-key-and-adding-it-to-the-ssh-agent).
+2. In your browser, go to [GIN > Your parameters > SSH keys](https://gin.g-node.org/user/settings/ssh).
+3. 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 :
+
+```bash
+datalad install git@gin.g-node.org:/LAAC-LSCP/XXX.git
+cd XXX
+```
+
+### Getting data
+
+You can get data from a dataset using the `datalad get` command, e.g.:
+
+```bash
+datalad get recordings/converted/ # download converted recordings
+datalad get annotations/*/converted/ # get converted annotations
+```
+
+Or:
+
+```bash
+datalad get . # get everything
+```
+
+You can download many files in parallel using the -J or --jobs parameters:
+
+```bash
+datalad get . -J 4 # get everything, with 4 parallel transfers
+```
+
+For more help with using DataLad, please refer to our [cheatsheet](https://childproject.readthedocs.io/en/latest/cheatsheet.html) or DataLad's own [cheatsheet](http://handbook.datalad.org/en/latest/basics/101-136-cheatsheet.html). If this is not enough, check DataLad's [documentation](http://docs.datalad.org/en/stable/) and [Handbook](http://handbook.datalad.org/en/latest/).
+
+### Fetching updates
+
+If you are notified of changes to the data, please retrieve them by issuing the following commands:
+
+```bash
+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`:
+
+```bash
+datalad remove -r path/to/your/dataset
+```
+
+
+## Maintainers
+
+Maintainers should install the dataset from LAAC-LSCP and run the setup procedure as follows:
+
+```bash
+datalad install git@gin.g-node.org:/LAAC-LSCP/tsimane2017.git
+cd tsimane2017
+datalad run-procedure setup --public --confidential
+```
+
+Changes should be pushed to origin, that will trigger a push to the others:
+
+```bash
+datalad push
+```
+
+## History
+
+>History of the dataset, add an entry to explain what was done at this point in time, example (from tsimane2017):
+- 2022-04 Alex Cristia processed files from Camila Scaff, resulting in data from XX children. These data came from copies of the back-up drives Lacie, hand-written notes, and re-listening to the audio files to determine date and child ID. Some of the processing was done by hand; other via a script called `gen-recordings.R`, which used to live in a dropbox folder shared between Alex and Camila.