What is GoodRelations?

GoodRelations is a vocabulary that can be used to exchange information about products and services, pricing, payment options, other terms and conditions, store locations and their opening hours, and many other aspects of e-commerce, between networks of computer systems. The focus is on interoperability between Web sites and clients consuming the information given on those sites.

In essence, GoodRelations defines

  1. a generic data structure
  2. unique identifiers for all elements of the data structure, i.e. its classes (entity types), properties (relationship types and attributes), and enumerated values (individuals).

GoodRelations is available as an OWL 2 DL Web ontology according to the W3C Web Ontology Language standard and can thus be used for exchanging data on the WWW, e.g. in Semantic Web and Linked Open Data projects. For more information, see the W3C Data Activity page.

GoodRelations is designed so that it fits

  1. any industry,
  2. any position in the value chain, and
  3. any country or legal environment.

It is a truly generic model of information for offering any kind of goods (e.g. cameras, cars, consulting, medical treatment, etc.) to others and for specifying the expected compensation (e.g. money or other goods in barter trade) and conditions (e.g. indicating the time your offer expires or the payment methods accepted).

What can I do with GoodRelations?

While it is impossible to enumerate everything one can do with GoodRelations, the most important usages are the following:

1. Search Engine Optimization for Google, Yahoo, Bing, and Yandex with Since November 2012, GoodRelations is the official e-commerce part of is an initiative driven by several major search engines and allows site-owners to mark-up information in their Web content so that search engines can extract and process it better, i.e. more reliably and with less effort.

In short, you can use the GoodRelations data model to add small data packets to your Web pages in HTML that represent your products and their features and prices, your stores and opening hours, payment options and the like. Search engines will then be able to understand your content better and trigger many positive effects for your site in the search results, like Google Rich Snippets, or individualized relevance ranking. For details, see GoodRelations for Semantic SEO.

2. Product Information Management (PIM/PDM) inside a single organization or a value chain: If you have to handle information about products and services from multiple sources, GoodRelations can serve as a global database schema for integrating the information, for it is typically easy to map existing data structures to GoodRelations. GoodRelations will then provide a common model to maintain, cleanse, consume, and share the data.

3. E-Commerce Data Quality Management: You can use GoodRelations to manage technical or commercial data from heterogeneous sources in graph databases (e.g. RDF triplestores) and implement data quality management projects on top of this model.

Overview of Features

  • Industry neutral: Suited for all kinds of products and services and all vertical industries, from consumer electronics to industrial parts and components or services.
  • B2B and B2C: Suited for information interchange between commercial entities and between companies and end-users.
  • All stages of the value chain: Can be used for information related to raw materials, manufacturing, wholesale, retail, after sales support, disposal, etc.
  • One vocabulary for many targets: GoodRelations markup will be honored by both traditional search engines (Google, Yahoo, Bing, Yandex), mobile applications, browser plug-ins, and future Linked Data / Semantic Web applications.
  • Multi-syntax: GoodRelations data can be expressed as Microdata in HTML, RDF (RDF/XML, Turtle, RDFa in HTML, JSON-LD inside HTML or stand-alone, NTriples), XML, dataRSS, OData, GData, and in many other syntaxes.
  • Flexible level of detail: Simple cases are simple, complex scenarios are fully supported. You can always publish as much data as you have without being required to lift your existing data to a rigid structure. See Dynamic Data Granularity.
  • Compatible with Facebook OGP: Can be combined with Facebook's Open Graph protocol.
  • Minimal impact on page size and loading times: Typically only ca. 1500 bytes of additional markup in Microdata or RDFa.
  • Conceptual coverage: Covers all essential elements of e-commerce information.
    • Products
      • Product features with unit of measurement information, support for open and closed ranges, enumerations, value references, etc.
      • Product models ("datasheets")
      • Product variants
      • Add-ons / optional extensions
      • Consumables and spare parts
    • Stores and sales locations
      • Opening hours
      • Seasonal opening hours
    • Company information
    • Commercial aspects of offers
      • Detailed pricing, including list prices, quantity discounts, and price ranges
      • Seasonal discounts
      • Prices for specific audiences
      • Delivery charges, also individually by region and carrier
      • Payment charges, also individually by region, payment method, and offer
      • Warranty scope and duration
    • Demand side, e.g. wish-lists and tendering
    • Ownership information, e.g. for global shopping histories