For example CALLHOME: Egyptian Arabic Speech Translation Corpus

The different subsets in the dataset if it is broken by dialects. For example,  Algerian , 2000, sentences. Put every subset in a new line in the format subset-name, number of samples, type [tokens sentences, documents]

Direct link to the dataset repository

for example https://huggingface.co/datasets/labr

Use shortcuts for example CC BY-SA 4.0,

Year of publishing the dataset/paper

used mixed if the dataset contains multiple dialects

brief description of the dataset

How many samples are in the dataset, this is closely related to the unit option. As an example if the dataset has 10K tweets you put the Volume: 10,000 and the Unit: sentences. Please don't use 10K or any abbreviations.

tokens usually used for ner, pos tagging, etc. sentences for sentiment analysis , documents for text modelling tasks

social media datasets are considered mid risks as they might release personal information, others might contain hate speech as well so considered as high risk.

Name of institution i.e. NYU Abu Dhabi

If the dataset is extracted or collected from another dataset put the name of such dataset

Direct link to the pdf of the paper i.e. https://arxiv.org/pdf/2110.06744.pdf

Is the dataset tokenized i.e الرجل = ال رجل

Where the data resides i.e. GitHub, GitLab, Kaggle, etc.

For example 1750 $

Does the dataset have validation / test split.

If you choose "Other" use comma to separate multiple tasks , i.e. sarcasm detection, abusive language detection, etc.

venue shortcut i.e. ACL

number of citations

Full name i.e Associations of computation linguistics

Add all authors split by comma

abstract of the published paper

put your full name in English