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Ideally, your data description includes the very elaborate questions outlined in
Datasheets for datasets by Gebru, Timnit, et al. (2018)1.
We strongly refer you to the original paper, which explains in detail the seven key ingredients of a proper dataset documentation.
Below, we have reproduced these questions, and we recommend you to include those as a
readme.txt, together with your datasets. For derived data, it may be enough to point to a relevant source code file, and provide a list of variables and their operationalization.
You can download a formatted version (
.docx) of this template using the button below. Alternatively, you can find a plain text version of it for copy & paste below.
A Shorter Version
That’s a lot of documentation. So - if you don’t have time, go with the bigger picture and answer the main questions only.
========================================================== D A T A S E T D E S C R I P T I O N ========================================================== Name of the dataset: ---------------------------------------------------------- 1. Motivation of data collection (why was the data collected?) [...] 2. Composition of dataset (what's in the data?) [...] 3. Collection process (how was the data collected?) [...] 4. Preprocessing/cleaning/labeling (how was the data cleaned, if at all?) [...] 5. Uses (how is the dataset intended to be used?) [...] 6. Distribution (how will the dataset be made available to others?) [...] 7. Maintenance (will the dataset be maintained? how? by whom?) [...]
Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., Daumé III, H., & Crawford, K. (2018). Datasheets for datasets. arXiv preprint arXiv:1803.09010. ↩︎