This part of the page description includes:
Posted: Sat Dec 28, 2024 7:15 am
As we can see from the screenshot above, the results are positioned on the left side of the page, while the rest of the SERP is dedicated to more information about any highlighted result.
Key URL links to landing pages
Key dates such as the time period covered by the data, when the dataset was last updated, and/or when it was first published.
Who provides the data
The data license
Its geolocation
A description of what data is
As Searchenginewatch.com points out by way of comparison, a search for the same keyphrase on “classic” Google in incognito mode gives priority to weather forecast results from Accuweather, the BBC, and the Met Office. So, having a search engine that focuses on pure, recorded data is certainly more useful.
Most (though not all) results make it clear to the user where business reviews the data comes from and what the original source is. And because the source is included in the Dataset Search SERP, we can be sure that clicking through to the site will provide access to the data we need.
Using Google Dataset Search to Increase Visibility
As a starting point for the service, Google has adopted Dataset Search, which is based on the work of webmasters who mark up their datasets with the Schema.org vocabulary .
Schema.org is a standardized way for developers to make information on their websites easy to crawl and understand by search engines. SEOs are probably familiar with Schema.org if only when they’ve marked up video content or other non-text objects on their sites, such as when they’ve optimized their business for local search.
There are many official guidelines and sources for dataset markup ( Schema.org homepage , Schema.org dataset markup list , Google's reference on dataset markup , and Google's webmaster forum ).
That’s why copywriters, journalists, and SEOs who consistently produce original data should seriously consider making their published data crawlable and accessible to Google.
This is why it would be a good idea to start this classification right away, if only because classifying data in Google Dataset Search is currently quite simple and immediate simply because the traffic to the service is not so massive at the moment, but certainly, in the short term, the race for ranking and positioning of hard data will be increasingly fierce.
Furthermore, the dataset markup will not only benefit your ranking in Dataset Search, but it will also increase your visibility for relevant data-centric queries that Google will certainly return in the SERP as well.
Hence the importance of this whole operation, since day after day we see more and more tables and statistics incorporated more and more frequently and in an increasingly intuitive way into different elements of the SERPs, such as, for example, the Knowledge Graph .
Key URL links to landing pages
Key dates such as the time period covered by the data, when the dataset was last updated, and/or when it was first published.
Who provides the data
The data license
Its geolocation
A description of what data is
As Searchenginewatch.com points out by way of comparison, a search for the same keyphrase on “classic” Google in incognito mode gives priority to weather forecast results from Accuweather, the BBC, and the Met Office. So, having a search engine that focuses on pure, recorded data is certainly more useful.
Most (though not all) results make it clear to the user where business reviews the data comes from and what the original source is. And because the source is included in the Dataset Search SERP, we can be sure that clicking through to the site will provide access to the data we need.
Using Google Dataset Search to Increase Visibility
As a starting point for the service, Google has adopted Dataset Search, which is based on the work of webmasters who mark up their datasets with the Schema.org vocabulary .
Schema.org is a standardized way for developers to make information on their websites easy to crawl and understand by search engines. SEOs are probably familiar with Schema.org if only when they’ve marked up video content or other non-text objects on their sites, such as when they’ve optimized their business for local search.
There are many official guidelines and sources for dataset markup ( Schema.org homepage , Schema.org dataset markup list , Google's reference on dataset markup , and Google's webmaster forum ).
That’s why copywriters, journalists, and SEOs who consistently produce original data should seriously consider making their published data crawlable and accessible to Google.
This is why it would be a good idea to start this classification right away, if only because classifying data in Google Dataset Search is currently quite simple and immediate simply because the traffic to the service is not so massive at the moment, but certainly, in the short term, the race for ranking and positioning of hard data will be increasingly fierce.
Furthermore, the dataset markup will not only benefit your ranking in Dataset Search, but it will also increase your visibility for relevant data-centric queries that Google will certainly return in the SERP as well.
Hence the importance of this whole operation, since day after day we see more and more tables and statistics incorporated more and more frequently and in an increasingly intuitive way into different elements of the SERPs, such as, for example, the Knowledge Graph .