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Case study: Hello, Cookie!

Published onMar 05, 2021
Case study: Hello, Cookie!

Hello, Cookie!
feat. Boris (1) + Sendhil (students, interfaces)
feat. Sendhil + team : schemas, roadmap


Goal, participants, purpose


  • A group gathering cookie recipes + turning them into collections

  • A set of cookie data-sources (from old books, from people)


  • Identify users and use cases to get feedback + measure progress

  • Structure schemas for each, define what parts of their use will touch R1 and other tools

  • Identify similar approaches for comparison + benchmarking

  • Atoms:

    • Ingredients

    • Measures

    • Tools

    • Actions

  • Derived atoms:

    • Substitutes (equivalence classes of ingredients)

    • Definitions (aliases; concepts — "what is a chocolate chip cookie?”)

    • Categories (folksonomy of tags applied to the above)

  • Recipes:

    • Recipe steps: combinations of atoms

    • Traditional recipes - sequences of steps + time + free description

    • Parametric recipes - models: tunable parameters + outcomes

  • Types of categories:

    • by input

    • by output

    • by materials

    • related filters

      • filter by what is available

      • fuzzy filtering w/ substitutes

Sharing recipes

  • Cookie book: 10 types, 100 recipes, 300 modules

  • Overview: atlas/feature-universe

    • find recipes by feature,

    • find a specific recipe

    • stats on top recipe requests

  • Recipe sharing

    • submit variant or new recipe

    • comment/review

Data sources

  • Data Catalog

    • Index of sources from books, sites, scrapers

    • Find a maintainer for each, ask for more uniform provenance + metadata

  • Glossaries and terms

  • Existing recipes

    • Mining old cookbooks (OCR + NLP)

    • Scrapable websites: often limited structure + persistence

  • Adjacent datasets :

    • In culture: Related music/art/books

    • For access: ingredient cost, nutrition, accessibility

    • For delight: taste graphs

  • Meta datasets: Food ontology: foodkg


  • Creating schemas to match a set of sources

  • Initial data entry by enthusiasts

    • Start by hand, with a spreadsheet for each schema / data source.

  • Chef League: Major choices that guide taste prefs (meat v veg, sugar or no), modeling exceptions (binaries for allergies, cilantros, durian)

Proposed targets

  • Collections w/ cookie recipes, definitions, and other data

    • Examples large (a cookbook) and small (all about one recipe)

  • Initial data others can query, view, ingest. (by October)

  • Articulate a contribution flow: how recipe writers, makers, testers add to collections

To incorporate

~ existing texts (Myhrvold team: scan+ocr; earlier work)
~ existing structured data : nutrition; diet substitutes; RDA
~~ existing ontologies: FoodOn, WD, FB. cuisines, KG connections
~ specialist data: cooking time; preservation-time in a fridge;
~ chef-specialties: techniques, reference works, taste clusters
~ categories: common classifiers (pescatarian, Atkins, Moroccan)
~ schemas: find/make a place to store + version schemas for food/cooking/recipes

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