Dinesafe Knowledge Base
  • Welcome
  • Return to DineSafe.com
  • Real-Time Norovirus Surveillance
    • Introduction
  • Methodology
  • Data Collection & Processing
  • Metrics & Indicators
  • Implementation Guidelines
  • FAQs
  • Benchmarking
    • Introduction
      • The Importance of Food Safety
      • Introduction to Our Benchmarking System and Its Purpose
      • Why Food Safety Benchmarking Matters: A Stakeholder Overview
    • Methodology & Systems
      • The Metrics We Use
        • Reports per 100 Stores
        • Reports per $1M Revenue
        • Persons Reported Sick per 100k Customers Served
      • Data Sources & Methodology
        • How We Gather Data
        • Estimating Data When Exact Figures Aren't Available
        • Ensuring Accuracy and Transparency
      • Our Benchmark Indexing System
        • Why We Use Indexing
        • Index Composition
        • Index Calculation Process
        • Understanding Index Comparisons
    • Case Study
      • Case Study - Chipotle Mexican Grill
    • Applications
      • Global Applicability of Our Benchmarking System
      • Product-Specific Benchmarking for Food Producers
    • Service Information
      • Why Subscribe to Our Benchmarking Service
      • Limitations & Considerations
      • Conclusion
      • FAQ
        • Q1: How often are the benchmarks updated?
        • Q2: Are the food poisoning reports reviewed before being included in the benchmarks?
        • Q3: How do you account for differences in restaurant size when comparing benchmarks?
        • Q4: Can restaurants submit their own data to improve the accuracy of the benchmarks?
        • Q5: How do your benchmarks relate to official health inspections and ratings?
        • Q6: How can businesses improve their benchmark scores?
  • Data Dictionary
    • Introduction
    • Primary Fields
    • Specialized Fields
    • Delivery Methods
    • Glossary
    • Further Questions
  • IWP Reporting Widget
    • Introduction
    • Why Our Widget? Key Features & Benefits
    • Embedding the Widget
      • How to Embed the Code
      • When to Use Simple Embedding Code vs Advanced Embedding Code
        • Benefits of the Advanced Embedding Code
        • Considerations When Using the Advanced Embedding Code
      • Test the Code
      • Standalone URL Option
      • Customization Options
      • Language Support
      • Mobile-Friendly Link
    • Data Management and Access
    • Compliance with FDA’s Voluntary National Retail Food Regulatory Program Standards
    • Examples of Embedded Widgets
    • FAQ
      • Q1: Who can use the Iwaspoisoned.com reporting widget and what is it?
      • Q2: How do I embed the widget on my website?
      • Q3: Is the widget customizable?
      • Q4: How do I access the reports?
      • Q5: How does the widget support FDA compliance?
  • Email Notifications
    • Introduction
    • Widget Email Alerts
Powered by GitBook
On this page
  • Locale Classification
  • Available Locale Types
  • Classification Logic
  • Usage Notes

Was this helpful?

Locale

Locale Classification

The locale field is a meta-classification that provides a standardized, high-level categorization of the reporting location. This classification is derived from multiple data points including place types, feature tags, and business categorizations, providing a simplified yet comprehensive way to understand the type of establishment involved.

Available Locale Types

Food Service

  • Restaurant - Traditional sit-down or quick-service restaurants

  • Food Truck - Mobile food vendors and food trucks

  • Cafe - Coffee shops and casual dining establishments

  • Bakery - Specialized bread and pastry establishments

  • Bar - Drinking establishments and pubs

Retail & Shopping

  • Grocery - Supermarkets and grocery stores

  • Convenience - Convenience stores and mini-marts

  • Department Store - Large retail establishments

  • Pharmacy - Drug stores and pharmacies

  • Furniture Store - Furniture and home goods retailers

  • Gas Station - Service stations and associated convenience stores

Transportation & Travel

  • Airport - Air transportation facilities

  • Airline-Inflight - Food service during flights

  • Transit Station - Bus stations, train stations, and other transit hubs

  • Cruise - Cruise ships and associated facilities

Education & Healthcare

  • School-University - Educational institutions, including colleges

  • Hospital - Medical facilities and healthcare centers

  • Nursing Home - Long-term care and assisted living facilities

Entertainment & Leisure

  • Theater - Movie theaters and entertainment venues

  • Stadium - Sports venues and large event spaces

  • Casino - Gaming establishments

  • Amusement - Theme parks and entertainment centers

  • Tourist Attraction - Points of interest and tourist destinations

Service & Delivery

  • Meal Delivery - Food delivery services

  • Lodging - Hotels and accommodation services

Classification Logic

The locale type is determined through a hierarchical analysis of:

  1. Feature tags (fetags) - Specific business identifiers

  2. Place types (place_types) - Google Places API classifications

  3. Business categorization buckets (bucket01, bucket02) - Internal business classifications

This provides a consistent way to group similar establishments while maintaining specificity where needed. For example, a university cafeteria and a public school would both be classified as "School-University", while a restaurant in an airport would be classified based on its primary function as "Restaurant".

Usage Notes

  • A single establishment can only have one locale classification

  • Classification follows a precedence order (e.g., feature tags take priority over place types)

  • The classification system is designed to be mutually exclusive and collectively exhaustive

  • New locale types may be added as needed to accommodate emerging business models

Last updated 6 months ago

Was this helpful?