> ## Content Index > Fetch the complete content index at: https://community.mozilladatacollective.com/llms.txt > Use this file to discover other available public pages before exploring further. # Datasheets: The Missing Manual for your Dataset - URL: https://community.mozilladatacollective.com/datasheets-the-missing-manual-for-your-dataset/ - Published: 2026-03-31T12:22:31.000Z - Updated: 2026-04-17T13:41:49.000Z - Description: In this video, produced by the Data Nutrition Project and illustrated by Jessica Yurkofsky, you'll learn more about the role of the datasheet and how you can use it to give clear guidance to potential downloaders about how your data can (and can't!) be used. - Author: Mozilla Data Collective - Tags: Guides 0:00 /3:51 1× When you [upload your dataset to Mozilla Data Collective](https://community.mozilladatacollective.com/uploading-your-dataset-to-the-mozilla-data-collective-platform/), creating a comprehensive datasheet is a critical part of the process. But what exactly is a datasheet? And how should you think about filling it out? Creating a comprehensive datasheet adds a lot more value to your dataset. It contextualizes the data that you are sharing, so that downloaders understand how it is intended to be used. ![](https://storage.ghost.io/c/ff/ca/ffcaf12e-8ea8-4d92-a7c4-6446e2c332cd/content/images/2026/03/image-2.png) The data card is the first preview that a downloader will have of your dataset. By being specific and clear in these fields, you can help people discover your dataset more easily. Once a potential downloader has found their way to your dataset, your datasheet will help them understand whether it's a good fit for their particular use case. ![](https://storage.ghost.io/c/ff/ca/ffcaf12e-8ea8-4d92-a7c4-6446e2c332cd/content/images/2026/03/image-3.png) The datasheet for the [Jember Javanese Spontaneous Speech Corpus](https://datacollective.mozillafoundation.org/datasets/cmlgm5a94008kny07nz2intus?ref=community.mozilladatacollective.com) on Mozilla Data Collective While only some fields in the dataset onboarding form are required, a thorough datasheet is a concrete tool to help individuals and communities share and govern their data. Join Mozilla Data Collective → ### Additional Resources [Turning Your Data Into a Valuable ML Resource Without Giving Up Control](https://community.mozilladatacollective.com/turning-your-data-into-a-valuable-ml-resource-without-giving-up-control/) \- This guide introduces the principles behind ethical data sharing, ownership, and documentation for community dataset creators [Datasheets for Datasets](https://www.microsoft.com/en-us/research/project/datasheets-for-datasets/?ref=community.mozilladatacollective.com) (Microsoft Research) - Accessible overview of the datasheet concept plus downloadable templates [Data Statements](https://techpolicylab.uw.edu/data-statements/?ref=community.mozilladatacollective.com) (UW Tech Policy Lab) - Practical framework specifically designed for language and speech datasets, including schema elements covering speaker demographics, annotator demographics, recording quality, and more. [Augmented Datasheets for Speech Datasets](https://github.com/SonyResearch/project%5Fethics%5Faugmented%5Fdatasheets%5Ffor%5Fspeech%5Fdatasets?tab=readme-ov-file&ref=community.mozilladatacollective.com) (Sony, GitHub Repo) - Sony Research's companion repo to the FAccT 2023 paper, containing the augmented speech datasheet template and completed example datasheets for five datasets including LibriSpeech and Common Voice [Datasheets for Datasets](http://arxiv.org/abs/1803.09010?ref=community.mozilladatacollective.com) Gebru et al. (2021) - The original paper proposing the datasheet framework, published in Communications of the ACM. Essential reading for understanding the motivation, design decisions, and scope of the datasheet standard [Data Statements for NLP](http://aclanthology.org/Q18-1041?ref=community.mozilladatacollective.com) Bender & Friedman (2018) - Proposes a complementary framework specifically for NLP/speech datasets, including speaker demographics, language variety (BCP-47 tags), recording quality, and speech situation; directly applicable to ASR and Common Voice datasets [The Dataset Nutrition Label](https://arxiv.org/abs/2201.03954?ref=community.mozilladatacollective.com) (2nd gen) Chmielinski et all (2022) - Offers an overview of the 2020 version of the Dataset Nutrition Label The Data Nutrition Project is empowering data practitioners and policymakers with tools to improve AI outcomes. [Learn more about the Data Nutrition Project ](https://datanutrition.org/?ref=community.mozilladatacollective.com) [Augmented Datasheets for Speech Datasets and Ethical Decision-Making](http://arxiv.org/abs/2305.04672?ref=community.mozilladatacollective.com) Papakyriakopoulos et al. (2023) - Extends Gebru et al.'s framework with speech-specific questions covering language diversity, accent, dialect, speech impairment, data subject protection, and speaker compensation. Grounded in a large literature review of SLT datasets. Published at ACM FAccT 2023\. The most directly relevant paper for documenting ASR datasets such as Common Voice [Data Statements: From Technical Concept to Community Practice](http://dl.acm.org/doi/full/10.1145/3594737?ref=community.mozilladatacollective.com) McMillan-Major, Bender & Friedman (2024) - Empirical follow-up on how practitioners actually use data statements, with refined schema (v3) and community-developed best practices [Navigating Dataset Cards on Hugging Face](http://arxiv.org/abs/2401.13822?ref=community.mozilladatacollective.com) (Research Analysis, 2024) - Large-scale empirical analysis of 7,400+ dataset cards on the Hub; reveals what documentation fields are most/least completed and what high-quality cards look like in practice --- ### Animation Credits Music by: Ricky Valadez Written by: Sarah Newman & Jessica Yurkofsky Illustrated by: Jessica Yurkofsky Read by: Sarah Newman Sound editing by: Halsey Burgund Special thanks to Liv Erickson, Katherine Reid, and Francis Tyers Produced by the [Data Nutrition Project](https://datanutrition.org/?ref=community.mozilladatacollective.com) in collaboration with [Mozilla Data Collective](https://mozilladatacollective.com/?utm%5Fsource=ghost&utm%5Fmedium=blog&utm%5Fcampaign=datasheet-video)