The GS1 Web Vocabulary is a new data standard that facilitates efficient and accurate exchange of structured, machine readable master data - products, locations, certifications etc - via the web, and following GS1 standards. In this guide, we'll dive deep into the GS1 Web Vocabulary, exploring its purpose, structure, benefits, and applications.
What is the GS1 Web Vocabulary?
The GS1 Web Vocabulary is a standardized data model designed to describe supply chain master data in a structured, machine-readable format. The current version covers products, locations, organizations and much more. Developed by GS1, a global non-profit organization responsible for supply chain standards (like barcodes and GTINs), this standard uses linked data principles to help businesses independently share consistent, structured product data that can be related together via links, in the same way that webpages from one business can link to another. By using GS1 Web Vocabulary, businesses can publish rich product data that is more easily discoverable, understandable, and usable by various systems, including e-commerce platforms, search engines, traceability systems and apps.
What does structured data mean and why do we need it?
Structured data refers to information that is organized in a specific, predefined format, making it easy for machines and programs to read, understand, and process. To understand why this is important, consider an example of a supermarket product purchase page:
As a human, we can easily guess that the heading at the top of this page is the product name, and the picture to the left of it is a picture of the product, and “£5.49” is the price. But all webpages are not the same. If we want to convey the same information to a machine, how can it be sure which element on the page refers to the product name, or price, or image? It is much better to express the data in a predefined format, so a program can be written that can extract these values from multiple online sources with confidence.
And this is exactly what is happening right now under the covers. If I search Google for this product, I might see a list like this:
Google can write a program that easily compiles this information because each individual site that wants to sell their product has agreed to also include a hidden set of “structured” data embedded in the webpage code. If you are interested, it looked like this for our original example:
Notice how the data model includes clear, consistent attribute names for data we are interested in, such as “price” and “description”. This data model for a “product” is defined publicly at an open source project called schema.org, where everyone can see the definition for each attribute. For example, here is the entry for the field “name”:
Introducing the GS1 Web Vocabulary
The work at schema.org is great, but incomplete for sharing supply chain information in a way that is aligned to GS1 standards. Therefore GS1 has created their own data model called the “GS1 Web Vocabulary” that extends the work done by schema.org and also incorporates work from other GS1 data standards for products, locations and more. To find it, navigate to https://ref.gs1.org/voc. Start by selecting “All Classes” from the menu top right:
With “All classes” selected, you will see a list of many different data entities that you can click on to explore. Here is a snippet from the top of the list:
The most interesting data entities relevant to supply chain traceability are:
- Product: Any item (product or service) that may be priced, or ordered, or invoiced at any point in any supply chain
- Place: Entities that have a fixed physical location
- Organization: Any legal entity or party involved at any point in any supply chain
- CertificationDetails: Certification issued by a certifying body to a certification subject (Organization, Place, Product).
If we click into these entities, we can see a list of all the field names, data types and descriptions, for example, net content and net weight in the Product entity:
Note that there are also sub-classes. For example there is a class called “Food Beverage Tobacco Product”, that extends Product, and therefore has all the fields that product has, but also has fields unique to food, beverage and tobacco, that wouldn’t necessarily apply to clothing for example:
How is GS1 Web Vocabulary data represented technically?
So what does a machine readable message using the GS1 Web Vocabulary look like? It is represented in a format called JSON-LD (JavaScript Object Notation for Linked Data), which is widely used by web developers. A really good tool to explore and create your own JSON-LD documents is provided by GS1 at https://www.gs1.org/1/smart-search-demo/
Let’s create the Coca Cola product from earlier by clicking through the wizard. Choose “Get Started”, then select currency and language:
Keep clicking through the wizard, selecting “Manufacturer”, “Product”, “Food and Beverage”, "Beverages". You will get to a screen like this, which we can start populating attributes about our product - in this example, Coca Cola:
There are many fields that can be filled. When we’ve finished, we can scroll to the bottom of the page and click “Create JSON-LD markup”:
A representation of our data in JSON-LD format is printed at the bottom of the page. Using this format, machines can confidently understand the product data we are trying to express:
How can we use the GS1 Web Vocabulary?
The historical use case for the GS1 Web Vocabulary is to provide structured information about products on the public internet that allow for the online commerce use cases we saw earlier. By including structured data in GS1 Web Vocabulary format, product data is more discoverable and searchable, and more accurate, especially when presented by third parties. Data is interoperable, easily understood by multiple independent parties in the supply chain.
But a second amazing use case is for cheap and easy master data exchange in supply chain traceability, without needing centralized systems or pre-configured system integration. As we learned in our GS1 EPCIS guide, supply chain events, such as manufacturing, packing and shipping, include references to locations and products, often expressed in Digital Link format. If a receiving traceability system receives an event that includes a location ID that it hasn’t encountered before, it could use a Digital Link “linkType” query to ask for machine readable data to understand where the location is, who owns it, how to contact staff there, and more. The GS1 Web Vocabulary provides a perfect data model to express and exchange this information, avoiding the need for complex, centralized master data exchange solutions. Check out this blog post where we explore this concept further.
Conclusion
The GS1 Web Vocabulary is a foundational framework that enables businesses to seamlessly share product and other master data information using the same underlying technologies that power the web. By leveraging the power of structured data, organizations can improve transparency, drive efficiency, and enhance their digital presence.
But the GS1 Web Vocabulary can be hard to navigate and implement effectively. At TrackVision AI, we provide software that allows you to upload product, location, organization and certification master data, generate Digital Links for all of them, and allow structured data representations of this data to be fetched programmatically in GS1 Web Vocabulary format. Contact us today to learn how you can apply this standard to lower traceability and data exchange costs in your supply chain.