Linked Data in the Wild

Hi, my name is Yulia and I'm a curriculum engineer at Inrupt. 

In this video we're going to find examples of how Linked Data Principles are used on the web. This, along with other technologies will help us chart a course to an interoperable future on the web. To learn more about interoperability or get an introduction to Linked Data, check out the links in the description.

In the previous video we introduced Linked Data Principles which are:

1. Use URIs as names for things 
2. Use URIs so that people can look up those names 
3. When someone looks up a URI, provide useful information 
4. Include links to other URIs so that they can discover more things 

We also discussed that the benefits of an interoperable ecosystem that uses Linked Data are in the common understanding of terms and context which is fostered by following these Linked Data Principles. In our example we discussed how each bit of useful information will include links to other information, making data self-describing and enriched with context. 

How can we accomplish this using URIs in such a way that it works for both machines and people? For one, we'll need commonly used vocabularies that define the terms that we use to describe our data. Since we want to find some Linked Data in the wild, we'll use Schema.org as our vocabulary example.

On their homepage it says that over 10 million sites use Schema.org to markup their webpages and email messages. One such use case example is described in their “Getting Started Docs” in the section called “Why use microdata?”.

"Web pages have an underlying meaning that people understand when they read the web pages. But search engines and applications have a limited understanding of what is being discussed on those pages. By adding additional tags to the HTML of web pages—tags that say, "Hey search engine, this information describes this specific movie, or place, or person, or video"—it helps search engines and other applications better understand the content and display it in a useful, relevant way." 

For example, right now when we search for an actor or a film that we are interested in, we get a lot of related information that we can browse through. If you are familiar with search engine optimization, then you know that these results are accumulated and presented nicely due to the presence of this microdata, which is really just a small subset of what Linked Data has to offer. 

Here we can see where this data has been pulled from. Some from Twitter, the videos are from Youtube, and since we looked up an actor, we see IMDB as the top source. 

Let's go to IMDB to see how exactly this data is retrieved by the search engine. 

https://www.imdb.com/name/nm0252961/?ref_=nv_sr_srsg_0 

First, we look for Idris Elba, then we open the developer tools. To find this microdata, we search for ld+ in the elements section. Ld, as you may have guessed, stands for Linked Data. ld+json is one of the ways to publish Linked Data to the web. 

We'll go through this form of Linked Data in later videos, but for now, we can see a reference to Schema.org, which in this case states that all the terms that we see in this web resource are defined by the Schema.org vocabulary, should we choose to look them up. 

Other fun things to look up are restaurants and hotels, or famous landmarks. Most of them have their data marked up with precise definitions from some vocabulary or another. Try it for yourself if you're curious.

For now, let's recap what we've learned.

In this video we searched for existing instances of Linked Data Principles being implemented on the web, and we found a subset of data that serves to improve search results for search engines. 

Through that we discovered a vocabulary called Schema.org, and a form of denoting Linked Data with JSON which can be found on page elements by searching for ld+json.

Using a Linked Data vocabulary in the right way allows data on the web to be self-describing, linkable, and machine-readable.

In the next video we'll dive deeper into Linked Data, beyond the context of search engine optimization. 

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