Open Food Facts Slack Notes: Data, Trends, and Discoveries

Open Food Facts is the largest and more comprehensive open database on the planet, by far.

The Open Food Facts Slack (open to all) has several channels for discussions, updates, and collaborations. I’ll keep sharing interesting facts I come across in the conversations there, right here:

* Pierre (teolemon) - The data (is)...legally acquired, through crowdsourcing and/or AI extraction from Crowdsourcing or existing OFF data. We don’t allow scraping for legal reasons.

* Alex Bourreau - I made a small tool to check what your contributions to Open Food Facts are used for : https://contributionreuses.bourreau.dev/

Enter your OFF username and it shows you a list of scientific articles that relied on data of products you've created !

* James Addison - OpenFoodFacts does have methods to detect products where errors seem likely; it tracks those errors and distributes them to registered volunteers, who then help by reviewing the errors, often fixing them where possible.

some links that I'd recommend:

an overview of the process: https://wiki.openfoodfacts.org/Data_quality

the errors that OFF detects: https://wiki.openfoodfacts.org/List_of_data_quality_errors_(generated)

data quality trends over time dashboard: https://mirabelle.openfoodfacts.org/-/dashboards/data-quality-dashboard

* Stephane - Open Food Facts computes the Nutri-Score, but the formula was created by the EREN research team, and then further developed at the European level

How is NOVA class calculated? Is the algorithm designated by the system, or is it made up for OFF?

* Pierre (teolemon) -  it’s following the Scientific paper of Pr. Monteiro, and we use a list of Ultra-processing markers defined in the paper to trigger NOVA 4, we also use categories in some cases as a supplement (like for Sodas where the whole category is NOVA 4)

* Tacite - If you mix two databases (your local + OFF), the OFF licence requires you to share your local database

* Stephane - OFF currently does not compute recommendations for alternative products. One option is to do a search query for the category of the product, and then rank products based on their nutrition etc.

W.I.P

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