LAION-AI / LAION-AI/Open-Assistant

Add the CosIng dataset (cosmetic ingredients)

Open
#1,871 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

data
Dominant language
Python
Stars
37.4k
Forks
3.3k
PR merge metrics
No merged PRs in 30d

Description

CosIng is an open EU dataset of cosmetic ingredients.

I think it's what websites like CosDNA or INCIdecoder are using with a few tweaks for better explainability.
Link to dataset (CSV available): https://data.europa.eu/data/datasets/cosmetic-ingredient-database-ingredients-and-fragrance-inventory?locale=en

It roughly follows this structure:

INCI name Chem/IUPAC Name / Description Restriction Function
DIPTEROCARPUS INTRICATUS EXTRACT (Dipterocarpus Intricatus Extract is the extract of the whole plant Dipterocarpus intricatus, Dipterocarpaceae. ANTIOXIDANT, HUMECTANT, SKIN CONDITIONING, SKIN CONDITIONING - EMOLLIENT
1,2-BUTANEDIOL HUMECTANT, SKIN CONDITIONING, SOLVENT, VISCOSITY CONTROLLING

The dataset could be converted to QA / instructional using this format:

Q: What is the <INCI name>?
A: Here is the short description or chemical name of this ingredient: <Chem/IUPAC Name / Description>. It's used as: <Function>

And for rows with empty descriptions:

Q: What is the <INCI name>?
A: I couldn't find a description for this ingredient. However, it's used as: <Function>

What do you think?

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

The issue provides the CosIng CSV link and two proposed QA templates, but names no repository file, test, or entry point. First determine where datasets and instructional QA examples are added; done would mean the dataset is converted according to the stated templates, including rows without descriptions.

Written by the indexing model from the issue text.

Assessment

Domain
data
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.