Lesson 2D: Make use of the structure, include Schema.org markup
Structure your data in a way search engines understand. Use Schema.org markup.
The transformation to the schema.org ontology is relevant since it is the vocabulary understood, and as a result mandated, by the search engines. The scope of Schema.org is to provide an extensive data model of objects commonly advertised on the web. Not all OGC feature types and properties can be transformed without loss of information to schema.org. For that reason schema.org supports extensions.
A shared markup vocabulary makes it easier for webmasters to decide on a markup schema and get the maximum benefit for their efforts. Search engines want to make it easier for people to find relevant information on the web. Markup can also enable new tools and applications that make use of the structure. Schema.org
Structured data including the Schema.org markup.
Step 1 is mapping features in datasets to schema.org. For example:
You can find relevant Schema.org classes here.
A GeoJSON to Schema.org converter is available here.
Not all OGC feature types and properties can be transformed without loss of information to schema.org. For that reason schema.org supports extensions.
In the second phase of the testbed we observed that domain experts include meaning into encodings like BU00030002 (BU = neighbourhood, 003 = Municipality with code 003, 00300 = a District in Municipality 003, 00300002 = a Neighbourhood in District 00300). In order to ‘open up’ this information to non-domain experts and machine processors, we have to interpret the meaning again by using a grammar.
[Google Structured Data Testing tool](https://developers.google.com/structureddata/ testingtool/)
