What is Structured Data and Why Should You Implement It?
Structured data is created by giving a machine readable document to an application. This document contains information about data fields, which allows the application to read and process the data. Structured data can be used to store data that is later used in an application. Structured data is also referred to as content or document-centric data because it is related to documents. This data can be stored in an XML text file or database and can describe the contents of a document. Structured data files are typically produced by computer programs. The program processes the text file, parses it into individual pieces of information, and then uses those pieces of information to generate a format that allows for easy input and output.
What is the Purpose of Structured Data
Structured data is currently transforming the way companies of all sizes do business with Google, marketers, and developers alike. Structured data is a set of standards for encoding information in a format that makes it easy for machines to understand and process, yielding significant benefits in terms of speed, accuracy, and access to data. When you develop data schemas, you can make it easy for your data to be processed automatically. As an example, suppose you want to find a recent purchase in your customer database. You can implement a schema that describes purchase transactions with only three fields: date, product, and cost. All of the values within these three fields will be handled by Google’s machine learning systems as part of the search algorithm so that when someone searches for “purchase” or any other value within this schema, they will find your data. The more structured your data is and the better it can be processed by machines, the more likely it is that Google will find it on a query. For example, suppose you have a schema that describes different types of soccer fields: hard or grass for instance. When someone searches for “soccer,” Google will be able to search through your database and find this type of information easily.
How to Implement Schema Markup with JSON-LD for your Website or Blog Post
How to Install Smart Plugins that Automatically Generate Schema Markup from Your Content
The JSON-LD webmaster tools API is a free, open-source, and unofficial API for google webmaster tools. It allows you to import or export data from or to your google webmasters account. By using the JSON format you can also make use of things like filters. Once you install the software, go to your google webmasters account and click on “tools” then “export data”. Then you’re able to export this data in the json format.
Some of the features:
1) You can easily see which domains have been crawled or not.
2) It exports data in a google friendly format, allowing you to import it into other tools such as SeoQuake or SEO PowerSuite.
3) It allows you to export your settings and imported settings.
4) You can export the crawl settings.
5) It is compatible with versions of the webmaster tool API (pre 1.9).
6) Export and import settings using your own CSV file formats.
7 ) Caching of data from google’s API.
8) Importing settings from one google webmasters tool to another.
9) Export your settings as a CSV file and import them into a different format or website.
10) Add/edit pages in the settings section.