Update 2022.02.21: We're close to launch! We're excited to have you!
Huggingface's BigScience🌸 initative is an open scientific collaboration of nearly 600 researchers from 50 countries and 250 institutions who collaborate on various projects within the natural language processing (NLP) space to broaden accessibility of language datasets while working on challenging scientific questions around language modeling.
We are running a Biomedical Datasets hackathon to centralize many NLP datasets in the biological and medical space. Biological data is often diverse, so a unified location that joins multiple sources while preserving the data closest to the original form can greatly help accessbility.
Our goal is to enable easy programatic access to these datasets using Huggingface's (🤗) datasets library. To do this, we propose a unified schema for dataset extraction, with the intention of implementing as many biomedical datasets as possible to enable reproducibility in data processing.
We are leveraging the 🤗 Community Hub in order to centralize these scripts so that practioners and researchers have easy access to these tools with a simple API.
There are two broad categories of biomedical datasets:
We will accept data-loading scripts for either type; please see the FAQs for more explicit details on what we propose.
Biomedical language data is highly specialized, requiring expert curation and annotation. Many great initiatives have created different language data sets across a variety of biological domains. A centralized source that allows users to access relevant information reproducibly greatly increases accessibility of these datasets, and promotes research.
Our unified schema allows researchers and practioners to access the same type of information across a variety of datasets with fixed keys. This can enable researchers to quickly iterate, and write scripts without worrying about pre-processing nuances specific to a dataset.
To be considered a contributor, participants must implement an accepted data-loading script to the bigscience-biomedical collection for at least 1 dataset.
Explicit instructions are found in Get started, but the overall criteria to get accepted is as follows:
- Write a data-loading script for a dataset in a new branch
- PR your branch to the
bigscience-biomedicalrepo and ping the admins - If an admin approves the PR, follow the instructions on uploading to the hub.
Details for contributor acknowledgements and rewards can be found here
Please make a github account prior to implement a dataset; you can follow instructions to install git here.
You will also need at least Python 3.6+. If you are installing python, we recommend downloading anaconda to curate a python environment with necessary packages. We strongly recommend Python 3.8+ for stability.
All commands in the guide provided are done through terminal access. If you need help, please reach out to an admin.
There are two options to choose a dataset to implement; you can choose either option, but we recommend option A.
Option A: Assign yourself a dataset from our curated list
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Choose a dataset from the list of Biomedical datasets.
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Assign yourself an issue by clicking the dataset in the project list, and comment
#self-assignunder the issue. Please assign yourself to issues with no other collaborators assigned. You should see your GitHub username associated to the issue within 1-2 minutes of making a comment. -
Search to see if the dataset exists in the 🤗 Hub. If it exists, please comment on the original issue with the link and choose another dataset to implement.
Option B: Implement a new dataset not on the list
If you have a biomedical or clinical dataset you would like to propose in this collection, you are welcome to make a new issue. Choose Add Dataset and fill out relevant information. Make sure that your dataset does not exist in the 🤗 Hub.
If an admin approves it, then you are welcome to implement this dataset and it will count toward contribution credit.
Check out our step-by-step guide to implementing a dataloader with the big-bio schema.
Please do not upload the data directly; if you have a specific question or request, reach out to an admin
Before your data-loading script is accepted, you will need to make a PR to the big-science biomedical repo. Explicit instructions on how to PR a dataloader are found here.
Once you do, an admin will code-review your changes. Admins may propose changes before acceptance, or accept as-is. Please feel free to reach out to get your PRs accepted!
Once the PR is accepted, please follow the instructions to upload the dataset into the Hub.
We welcome contributions from a wide variety of backgrounds; we are more than happy to guide you through the process. For instructions on how to get involved or ask for help, check out the following options:
Please join the BigScience initiative here; there is a google form to fill out to have access to the biomedical working group slack. Once you have filled out this form, you'll get access to BigScience's google drive. There is a document where you can fill your name next to a working group; be sure to fill your name on the "Biomedical" group.
Alternatively, you can ping us on the Biomedical Discord Server. The Discord server can be used to share information quickly or ask code-related questions.
For quick questions and clarifications, you can make an issue via Github.
You are welcome to use any of the above resources as necessary.
We understand that some biomedical datasets require external licensing. To respect the agreement of the license, we recommend implementing a dataloader script that works if the user has a locally downloaded file. You can find an example here and follow the local/private dataset specific instructions in template.
We understand that some biomedical datasets require external licensing. To respect the agreement of the license, we recommend implementing a dataloader script that works if the user has the dataset file(s) stored locally. You can find an example here.
Eventually, your dataloader script will need to run using only the packages supplied by the datasets package. If you find a well supported package that makes your implementation easier (e.g. bioc), then feel free to use it.
We will address the specifics during review of your PR to the BigScience biomedical repo and find a way to make it usable in the final submission to huggingface bigscience-biomedical
No. Please do not upload your dataset directly. This is not the goal of the hackathon and many datasets have external licensing agreements. If the dataset is public (i.e. can be downloaded without credentials or signed data user agreement), include a downloading component in your dataset loader script. Otherwise, include only an "extraction from local files" component in your dataset loader script. You can see examples of both in the examples directory. If you have a custom dataset you would like to submit, please make an issue and an admin will get back to you.
In some cases, a single dataset will support multiple tasks with different bigbio schemas. For example, the muchmore dataset can be used for a translation task (supported by the text_to_text schema) and a named entity recognition task (supported by the kb schema). In this case, please implement one config for each task and name the config bigbio-<task>. In the muchmore example, this would mean one config called bigbio-translation and one config called bigbio-ner.
Full details on how to handle offsets and text in the bigbio kb schema can be found in the schema documentation.
Yes! Please join the hack-a-thon Biomedical Discord Server and ask for help.
Yes! Some datasets are easier to write dataloader scripts for than others. If you find yourself working on a dataset that you can not make progress on, please make a comment in the associated issue, asked to be un-assigned from the issue, and start the search for a new unclaimed dataset.
We greatly appreciate your help - as a token or our gratitude, contributors can get the following rewards:
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Authorship on a paper; we are submitting this work to various venues centered on programmatic access to biomedical literature
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Recognition as an official contributor if your script is accepted, you will be an official author on the BigScience Biomedical library from Huggingface.
The hackathon guide is heavily inspired from here.