Difference between revisions of "GSOC 2022 - Taxonomy editor"

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=== Project 7: Build a taxonomy editor ===
 
=== Project 7: Build a taxonomy editor ===
 
Description:  
 
Description:  

Revision as of 13:16, 12 April 2022

Project 7: Build a taxonomy editor

Description:

Taxonomies are at the heart of openfoodfacts in many aspects. It helps identify components (ingredients, labels, brands,…) and link them to useful properties, at the base of nutri-score, eco-score, allergens identification and some other properties.

Each taxonomy is a DAG (directed acyclic graph) where leaves have one or more parents. Currently the taxonomy is in a raw text file in our repository: https://github.com/openfoodfacts/openfoodfacts-server/tree/main/taxonomies.

While effective for the application, this format is quite cumbersome to edit for contributors.

We would like to have a tool (online or standalone) to edit taxonomies.

Expected outcomes:

The tool should:

  • help quickly find an element with a search
  • help visualize the hierarchy of components
  • help visualize the component, it’s synonyms in multiple languages
  • indicate inherited properties for an element, and signal when there are more than one
  • enable edition of those names, synonyms and properties
  • run some validation on names, synonyms and properties (no duplicate, specific formats, etc.)

As a bonus, it would be really interesting to know the impact of a modification on the application. For that we could imagine simple API’s (one for each taxonomy) on the openfoodfact application to visualize which products would be affected by a change. This feedback could be a really interesting tool to ensure no error is made (unexpected side effects)

Technologies: On the technical side, you can choose freely, in accordance with your mentor, which technology to use, still the capacity for the contributors community to maintain it in the long run is an important criteria.

Skills required/preferred: The candidate should be creative, but also have a good logical thinking capacity and also be able to track possible problems ahead.

  • Slack channels: #taxonomies
  • Potential mentors: Stéphane Gigandet / Alexandre Garel
  • Project duration: 350h
  • Difficulty rating: Medium