FoodMapr

This is a derived work from LexMapr that focuses on food items and products.

What are the differences:

• Include the English stop words as the default.

• Remove the functionalities to output the text buckets and classifications.

• Remove the micro and macro match statuses.

• Introduce a new profile called "anz" to map the Australia New Zealand Food Standards to the Food Ontology concepts.

  $ foodmapr input.csv -p anz -o output.json
  

Installation

1. Install Conda.

2. Create a FoodMapr environment

   $ conda create --name FoodMapr
   

3. Install FoodMapr into your conda environment:

   $ conda activate FoodMapr
   $ git clone https://github.com/protegeteam/foodmapr.git
   $ cd foodmapr
   $ pip install .
   $ python -m nltk.downloader punkt
   $ python -m nltk.downloader stopwords
   

4. (Optional) Set an environment variable USER_NLTK_DATA for a user-defined NLTK data location

   $ export USER_NLTK_DATA=/path/to/nltk_data
   

   Alternatively, edit .bash_profile and add the environment variable to make it available at startup

Usage

1. Prepare the input file: food.csv

   FoodId,FoodName
   F001,Chicken Breast
   F002,Baked Potato
   F003,Canned Corn
   F004,Frozen Yogurt
   F005,Apple Pie
   

2. Prepare the configuration file: config_foodon.json

   [
      { "http://purl.obolibrary.org/obo/foodon.owl": [
           "http://purl.obolibrary.org/obo/FOODON_00001871",
           "http://purl.obolibrary.org/obo/FOODON_00002373",
           "http://purl.obolibrary.org/obo/FOODON_00002381",
           "http://purl.obolibrary.org/obo/FOODON_00002645",
           "http://purl.obolibrary.org/obo/FOODON_00001180",
           "http://purl.obolibrary.org/obo/FOODON_03311737",
           "http://purl.obolibrary.org/obo/FOODON_00001714"
        ]
      }
   ]

3. Run the command on the Terminal console

   (FoodMapr) foo@bar:~$ foodmapr food.csv -c config_foodon.json
   {
      "mapping_output": {
         "Chicken Breast:F001": "chicken breast:FOODON_00002703",
         "Baked Potato:F002": "potato (whole, baked):FOODON_03302196",
         "Canned Corn:F003": "corn (canned):FOODON_03302665",
         "Frozen Yogurt:F004": "frozen yogurt:FOODON_03307445",
         "Apple Pie:F005": "apple pie:FOODON_00002475"
      },
      "input_to_ontology_mapping": {
         "F001": "FOODON_00002703",
         "F002": "FOODON_03302196",
         "F003": "FOODON_03302665",
         "F004": "FOODON_03307445",
         "F005": "FOODON_00002475"
      },
      "ontology_to_input_mapping": {
         "FOODON_00002703": "F001",
         "FOODON_03302196": "F002",
         "FOODON_03302665": "F003",
         "FOODON_03307445": "F004",
         "FOODON_00002475": "F005"
      },
      "input_term_label": {
         "F001": "Chicken Breast",
         "F002": "Baked Potato",
         "F003": "Canned Corn",
         "F004": "Frozen Yogurt",
         "F005": "Apple Pie"
      },
      "ontology_term_label": {
         "FOODON_00002703": "chicken breast",
         "FOODON_03302196": "potato (whole, baked)",
         "FOODON_03302665": "corn (canned)",
         "FOODON_03307445": "frozen yogurt",
         "FOODON_00002475": "apple pie"
      }
   }